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GTC On-Demand

Artificial Intelligence and Deep Learning
Presentation
Media
Opening Keynote
Jensun Huang (NVIDIA)
The GTC Europe 2018 opening keynote delivered by NVIDIA Founder and CEO, Jensen Huang, speaking on the future of computing. ...Read More

The GTC Europe 2018 opening keynote delivered by NVIDIA Founder and CEO, Jensen Huang, speaking on the future of computing.

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Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8001
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AI for Business
Presentation
Media
Deep Learning Demystified
Will Ramey (NVIDIA)
See how deep neural networks are trained to perform tasks with super-human accuracy and will explore which deep neural network models are best-suited for a variety of tasks.
See how deep neural networks are trained to perform tasks with super-human accuracy and will explore which deep neural network models are best-suited for a variety of tasks.  Back
 
Keywords:
AI for Business, GTC Europe 2018 - ID E8110
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The Big Trends in AI and How They are Affecting Companies
Andreas Liebl (Applied AI), Andreas Braun (Accenture)
Explore the worldwide trend of implementing AI and Deep Learning solutions across a range of vertical markets as well as how they are a game-changing factor for the workflows of a company.
Explore the worldwide trend of implementing AI and Deep Learning solutions across a range of vertical markets as well as how they are a game-changing factor for the workflows of a company.  Back
 
Keywords:
AI for Business, GTC Europe 2018 - ID E8231
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Why Invest in AI and Deep Learning?
David Controle (Airbus)
Explore the benefits linked to investing in AI and deep learning. The journey from the decision making stage to implementation and the benefits to each business area within a company will be shown through real-life use cases.
Explore the benefits linked to investing in AI and deep learning. The journey from the decision making stage to implementation and the benefits to each business area within a company will be shown through real-life use cases.   Back
 
Keywords:
AI for Business, GTC Europe 2018 - ID E8413
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How to Create Talented Teams and Deliver Successful AI Solutions
Micael HOLMSTROEM (Academy.se), Will Ramey (NVIDIA), Timo Stich (Zeiss), Ulli Waltinger (Siemens)
This panel will showcase how management teams can implement new AI/DL solutions quickly and effectively, by developing talented teams successfully. It will also discuss how POCs can be moved seamlessly into productive use. ...Read More

This panel will showcase how management teams can implement new AI/DL solutions quickly and effectively, by developing talented teams successfully. It will also discuss how POCs can be moved seamlessly into productive use.

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Keywords:
AI for Business, GTC Europe 2018 - ID E8417
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Women At GTC Lunch: "Leadership In The Age of AI"
Polina Mamoshina (NVIDIA), Vidya Munde Müller (Women in AI Ambassador, Germany), Silja Pieh (Autonomous Intelligent Driving GmbH)
This session will feature at the Women at GTC Lunch event and will explore the topic of "Leadership In The Age of AI". All attendees who support diversity and inclusion in the tech world are welcome to join.
This session will feature at the Women at GTC Lunch event and will explore the topic of "Leadership In The Age of AI". All attendees who support diversity and inclusion in the tech world are welcome to join.   Back
 
Keywords:
AI for Business, Artificial Intelligence and Deep Learning, Autonomous Driving, Virtual and Augmented Reality, Bioinformatics, GTC Europe 2018 - ID E8497
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Inception Awards
GTC Europe will feature groundbreaking work from startups using artificial intelligence to transform the world in the fields of autonomous machines, cyber security, healthcare and more. Join us to watch the hottest startups in Europe take to the ...Read More

GTC Europe will feature groundbreaking work from startups using artificial intelligence to transform the world in the fields of autonomous machines, cyber security, healthcare and more. Join us to watch the hottest startups in Europe take to the stage and pitch their work for a chance to win $100,000 and a DGX Station.

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Keywords:
AI for Business, Artificial Intelligence and Deep Learning, Virtual and Augmented Reality, Autonomous Driving, Autonomous Machines, GTC Europe 2018 - ID E8499
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Artificial Intelligence and Deep Learning
Presentation
Media
Deep Learning Implementers Panel: Field Insights for Accelerating Deep Learning Performance, Productivity and Scale
Tony Paikeday (NVIDIA), Georgi Kadrev (Imagga), Sunil Mistry (SCAN), Damian Borth (University of St. Gallen)
This European customer panel brings together A.I. implementers who have deployed deep learning at scale using NVIDIA DGX Systems. We'll focus on specific technical challenges we faced, solution design considerations, and best practices learne ...Read More
This European customer panel brings together A.I. implementers who have deployed deep learning at scale using NVIDIA DGX Systems. We'll focus on specific technical challenges we faced, solution design considerations, and best practices learned from implementing our respective solutions. Attendees will gain insights such as: 1) how to set up your deep learning project for success by matching the right hardware and software platform options to your use case and operational needs; 2) how to design your architecture to overcome unnecessary bottlenecks that inhibit scalable training performance; and 3) how to build an end-to-end deep learning workflow that enables productive experimentation, training at scale, and model refinement.  Back
 
Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8114
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Intellectual Property Protection for Distributed Neural Networks
Neural Networks have capitalized on recent advances on HPC, GPUs, GPGPUs, and the rising amounts of publicly available labeled data. In doing so, NN have and will revolutionize virtually every current application domain, as well as enable novel ...Read More

Neural Networks have capitalized on recent advances on HPC, GPUs, GPGPUs, and the rising amounts of publicly available labeled data. In doing so, NN have and will revolutionize virtually every current application domain, as well as enable novel ones such as those on recognition, autonomous, predictive, resilient, self-managed, adaptive, and evolving applications.
Nevertheless, it is to point out that NN training is rather resource intensive in data, time and energy; turning the resulting trained models into valuable assets represents an IP imperatively worth of being protected.
Furthermore, in the wake of Edge computing, NNs are progressively deployed across decentralized landscapes; as a consequence, IP owners are very protective of their NN based software products.
In this session, we propose to leverage Fully Homomorphic Encryption (FHE) to protect simultaneously the IP of trained NN based software and the input and the output data.
Within the context of a smart city scenario, we outline our NN model-agnostic approach, approximating and decomposing the NN operations into linearized transformations while employing a SIMD for vectorization.

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Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8147
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How we Enhanced 1 200 000 Sub-Sea AUV Images with AI and CUDA
A Norwegian oil company needed to fix 1 million images of seabed, taken with artificial light, to be able to create a geological orthophoto. Due to light absorption in the water, all images were bright in center and dark at the sides. The poor q ...Read More

A Norwegian oil company needed to fix 1 million images of seabed, taken with artificial light, to be able to create a geological orthophoto. Due to light absorption in the water, all images were bright in center and dark at the sides. The poor quality of these images stopped us from machine analysis, so we used NVIDIA CUDA to create a routine that automatically analyzed all images one by one and fixed the inconsistent lighting. Afterwards, the images could be analysed with machine learning. The routine analysed every image separately and repaired them automatically.

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Keywords:
Artificial Intelligence and Deep Learning, Bioinformatics, GTC Europe 2018 - ID E8148
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The Journey from a Small Development Lab Environment to a Production GPU Inference Datacenter
Markus Weber (NVIDIA), Ryan Olson (NVIDIA)
We'll do a dive deep into best practices and real world examples of leveraging the power and flexibility of local GPU workstations, such as the DGX Station, to rapidly develop and prototype deep learning applications. This journey will take y ...Read More
We'll do a dive deep into best practices and real world examples of leveraging the power and flexibility of local GPU workstations, such as the DGX Station, to rapidly develop and prototype deep learning applications. This journey will take you from experimenting and iterating fast and often, to obtaining a trained model, to eventually deploying scale-out GPU inference servers in a datacenter. Tools available, that will be explained, are NGC (NVIDIA GPU Cloud), TensorRT, TensorRT Inference Server, and YAIS.  Back
 
Keywords:
Artificial Intelligence and Deep Learning, HPC and Supercomputing, GTC Europe 2018 - ID E8150
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Protecting Pulsed High-Power Lasers with Real-Time Object Detection
Jeffrey Kelling (Helmholtz-Zentrum Dresden - Rossendorf)
Learn how to train and employ state-of-the-art object localization in a real-time safety application. In Petawatt laser systems, firing at 10Hz, suddenly appearing scatterers can damage components. Damage(-spreading) can be avoided by suspending ...Read More

Learn how to train and employ state-of-the-art object localization in a real-time safety application. In Petawatt laser systems, firing at 10Hz, suddenly appearing scatterers can damage components. Damage(-spreading) can be avoided by suspending operation immediately upon occurrence of such an event.

We present our approach for the automatic detection of critical failure states from intensity profiles of the laser beam. In order to minimize the rate of false alarms, which would reduce productivity or even render our system useless, we refrain from general anomaly detection and instead detect known error patterns. In this talk we present how we fitted the You Look Only Once(YOLO) approach, which is suited to low-latency object detection, to our problem and how we adapted the required multi-step training protocol to the available experimental data.

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Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8170
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Real World Application of Multi-Agent Deep Reinforcement Learning: Autonomous Traffic Flow Management
Erik Nygren (Swiss Federal Railways), Adrian Egli (Swiss Federal Railways)
In this session we would like to demonstrate the benefits of multi-agent reinforcement learning for real world applications. We highlight our multi-agent system which is capable to learn an efficient communication protocol. The agents transmit r ...Read More

In this session we would like to demonstrate the benefits of multi-agent reinforcement learning for real world applications. We highlight our multi-agent system which is capable to learn an efficient communication protocol. The agents transmit relevant information through a low bandwidth channel to collectively solve a complex rescheduling problem. This approach proves beneficial whenever a feasible solution needs to be found within a short timeframe - in contrast to the computationally expensive optimal solution. Thus, our results can be applied to many different problems in the domain of operations research and transportation.
Key words: Deep Learning and AI, DGX, Reinforcement Learning, Traffic Management

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Keywords:
Artificial Intelligence and Deep Learning, HPC and Supercomputing, GTC Europe 2018 - ID E8219
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Deep Reinforcement Learning for Partially Observable Environments: Learning to Reason about Uncertainty
Maximilian Igl (University of Oxford)
We will present "Deep Variational Reinforcement Learning for POMDPs" (DVRL), a state-of-the-art algorithm to handle uncertainty in partially observable environments. To make the step from the ivory tower into the real world, i ...Read More

We will present "Deep Variational Reinforcement Learning for POMDPs" (DVRL), a state-of-the-art algorithm to handle uncertainty in partially observable environments.

To make the step from the ivory tower into the real world, it is important for autonomous agents to learn how to deal with missing information. This can, for example, occur when sensors are noisy, objects are occluded in videos or the underlying disease of a patient is still unknown.

In contrast to previous approaches, our agent learns a generative model of its surroundings and uses it to explicitly reason about the true (unseen) world state. This requires additional computations that can be executed in parallel on a GPU: GPUs in reinforcement learning are often under-utilized when performing the action is the bottleneck, especially when the environment cannot be easily simulated or the agent is trained on-policy.
We show the success of our approach on two environments, including the standard benchmark tasks in the Atari Learning Environment.

Familiarity with Reinforcement Learning will be helpful but is not required.
This work was generously supported by NVIDIA, providing access to DGX-1s for running experiments.

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Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8259
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Inside NVIDIA GPU Cloud Containers
Chris Kawalek (NVIDIA), Michael O'Connor (NVIDIA)
In this technical deep dive, get an in-depth look at the GPU-accelerated containers for deep learning and high performance computing available on NVIDIA GPU Cloud (NGC) and learn how they can simplify your projects. NVIDIA pre-integrates and opt ...Read More

In this technical deep dive, get an in-depth look at the GPU-accelerated containers for deep learning and high performance computing available on NVIDIA GPU Cloud (NGC) and learn how they can simplify your projects. NVIDIA pre-integrates and optimizes the top deep learning software such as TensorFlow, PyTorch, MXNet, and TensorRT, and makes it available on NVIDIA GPU Cloud, removing time consuming do-it-yourself software integration. We'll look at the NVIDIA framework optimizations, such as reducing GPU memory overhead, improving multi-GPU scaling, and reducing latency. We'll also talk about the integration of runtimes and drivers in the containers to ensure the best versions are all working together for peak performance. You'll leave with an understanding of what makes an NVIDIA GPU Cloud container tick.

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Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8270
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Fashion Design with GANs: Disentangling Color, Texture, and Shape
Gökhan Yildirim (Zalando SE)
Explore a new approach in GPU-aided Fashion Design with Generative Adversarial Networks (GAN). We propose a deep-learning method that independently controls the color, texture, and shape of a generated clothing article. In this session, we will show ...Read More
Explore a new approach in GPU-aided Fashion Design with Generative Adversarial Networks (GAN). We propose a deep-learning method that independently controls the color, texture, and shape of a generated clothing article. In this session, we will show how we disentangled the effect of input attributes by customizing a conditional GAN architecture with consistency-ensuring loss functions. Thanks to our GPU-based model, we will visually demonstrate rapidly-prototyped garments by designing and tuning their characteristics.  Back
 
Keywords:
Artificial Intelligence and Deep Learning, Professional Visualisation, GTC Europe 2018 - ID E8289
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Infrastructure choices for machine learning and deep learning- Presented by CISCO
Ravi Mishra (Cisco Systems Inc), Vikas Ratna (Cisco)
In this session, you will learn what factors to consider when making infrastructure choices and what the benefits of on-premise infrastructure are for machine learning and deep learning. When considering artificial intelligence and machine learning, ...Read More
In this session, you will learn what factors to consider when making infrastructure choices and what the benefits of on-premise infrastructure are for machine learning and deep learning. When considering artificial intelligence and machine learning, model development and algorithm choices are key. But anybody who attempted to train a model on a full dataset will tell you that infrastructure matters, a lot in fact. You can save hours, days, and sometime weeks by running your training algorithm on the right GPU-accelerated infrastructure. On the other hand when hunting for the perfect model for your business problems, you need to be able to stand up infrastructure quickly, connect to the existing data lake and iterate through many, many algorithm variations.   Back
 
Keywords:
Artificial Intelligence and Deep Learning, AI for Business, GTC Europe 2018 - ID E8356
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Machine Learning Techniques for Track Reconstruction at the CMS Experiment
Maurizio Pierini (CERN)
Starting from 2020, the increased accelerator luminosity of the Large Hadron Collider at CERN will directly result in an increased number of simultaneous proton-proton collisions (pile-up) which will pose significant new challenges for the CMS experi ...Read More
Starting from 2020, the increased accelerator luminosity of the Large Hadron Collider at CERN will directly result in an increased number of simultaneous proton-proton collisions (pile-up) which will pose significant new challenges for the CMS experiment. The adoption of machine learning techniques, along with traditional algorithms implemented on GPUs for both training and online inference, would reduce the incremented workload for the track reconstruction and improve the event selection.   Back
 
Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8363
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What is Needed to Industrialise Deep Learning?
Jonathan Berte (RoboVision)
At RoboVision we built an industrial pipeline that starts from scalable data curation to on premise deployment. Our goal is to put the internal teams at the customer in the driving seat, making them able to generate powerful deep learning models ...Read More

At RoboVision we built an industrial pipeline that starts from scalable data curation to on premise deployment. Our goal is to put the internal teams at the customer in the driving seat, making them able to generate powerful deep learning models, deploying them, and getting more value from their DGX1 investments, without lengthy consultancy. With android integration and predictive labeling we enable a big crowd to annotate data, directly accessible for multi-gpu deep learning sessions. The data is stored on high speed storage systems like Pure. The tool uses nifty techniques like predictive labeling and multi-user curation to guarantee high quality input for the configurable deep learning stack. This stack is made scalable and robust, with the help of Kubernetes and MySQL clusters, ending in a restful API system for rapid integration in the client's ecosystem. After pioneering diverse applications in agriculture, RoboVision expanded its focus and is now active in industrial automation, safety and security, smart city and surveillance markets.

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Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8366
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GPU Coder: Automatic integration of MATLAB with TensorRT
Ram Kokku (MathWorks), Bill Chou (MathWorks)
Learn how GPU Coder produces high-performance CUDA code automatically from a high-level algorithm description in MATLAB. Write your deep learning application with the expressive power of MATLAB, which allows you to describe not just the use of your t ...Read More
Learn how GPU Coder produces high-performance CUDA code automatically from a high-level algorithm description in MATLAB. Write your deep learning application with the expressive power of MATLAB, which allows you to describe not just the use of your trained deep learning model in inference mode but also perform data-augmentation and post-processing of the results to create a complete deployment-ready application. GPU Coder can then generate optimized inference code for the whole application. The deep learning inference model is compiled down to TensorRT, while the rest of the application logic is parallelized through creation of CUDA kernels and integration with other CUDA optimized libraries like cuBLAS, cuFFT, etc. The generated code can be cross-compiled to any NVIDIA GPU device that supports TensorRT. This allows engineers and scientists to unlock the expressive ease-of-use of the MATLAB programming language while unleashing deep learning performance by leveraging TensorRT.  Back
 
Keywords:
Artificial Intelligence and Deep Learning, Autonomous Driving, GTC Europe 2018 - ID E8370
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The Dynamics of Generative Adversarial Networks
Lars Mescheder (Max Planck Institut für Intelligente Systeme)
Learn about new perspectives on Generative Adversarial Networks (GANs) based on dynamical systems theory. In this session, I will show how dynamical system theory widens our understanding of GANs and provides us with powerful tools for analyzing thei ...Read More
Learn about new perspectives on Generative Adversarial Networks (GANs) based on dynamical systems theory. In this session, I will show how dynamical system theory widens our understanding of GANs and provides us with powerful tools for analyzing their convergence and stability properties. Using these tools, we analyze the behavior of common training algorithms for GANs and derive new methods that are both effective and computationally efficient. Our experiments demonstrate that such methods enable stable training of GANs for high resolution image distributions without the need for excessive hyperparameter tuning.  Back
 
Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8401
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Large-Scale AI Deployments with Kubernetes on NVIDIA GPUs
Renaud Gaubert (NVIDIA)
In this session we'll explore some of the common challenges with scaling-out deep learning training and inference deployment on data centers and public cloud using Kubernetes on NVIDIA GPUs. Through examples we'll review a typical workfl ...Read More

In this session we'll explore some of the common challenges with scaling-out deep learning training and inference deployment on data centers and public cloud using Kubernetes on NVIDIA GPUs. Through examples we'll review a typical workflow for AI deployments on Kubernetes. We'll discuss advanced deployment options such as deploying to heterogenous GPU clusters, specifying GPU memory requirements, and analyzing and monitoring GPU utilizations using NVIDIA DCGM, Prometheus and Grafana.

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Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8411
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An Efficient CUDA-Accelerated Machine Learning Inference for 4G and 5G Radio Networks
Tero Rissa (Nokia)
We describe the design of scalable CUDA-based service framework for ML model inference tasks to efficiently distribute such workloads across a cluster of dedicated GPU-based servers. These servers can also be easily integrated with existing telecom c ...Read More
We describe the design of scalable CUDA-based service framework for ML model inference tasks to efficiently distribute such workloads across a cluster of dedicated GPU-based servers. These servers can also be easily integrated with existing telecom cloud infrastructure. In telecom data centres, ML models are increasingly being deployed for use cases such as automation, analytics and anomaly detection. Handling diverse datatypes and request rates ranging between hours and milliseconds can become a challenge with a legacy CPU-dominated cloud environment.   Back
 
Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8421
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Machine Learning Enabled 5G Wireless Networks: GPU Convex Feasibility Solvers
Slawomir Stanczak (Technical University Berlin and Fraunhofer Heinrich-Hertz-Institute Berlin)
In current wireless networks, most algorithms are iterative and might not be able to meet the requirements of some 5G technologies such as ultra-reliable low-latency communication within a very low latency budget. For instance, requiring and end ...Read More

In current wireless networks, most algorithms are iterative and might not be able to meet the requirements of some 5G technologies such as ultra-reliable low-latency communication within a very low latency budget. For instance, requiring and end-to-end latency below 1ms, many signal processing tasks must be completed within microseconds. Therefore, only a strictly limited number of iterations can be performed, which may lead to uncontrollable excessive errors.

We argue in favor of formulating the underlying optimization problems as convex feasibility problems in order to enable massively parallel processing on GPUs for online learning for fast and robust tracking. Moreover, convex feasibility solvers allow for an efficient incorporation of context information and expert knowledge, and can provide robust results based on relatively small data sets. Our approach has numerous applications, including channel estimation, peak-to-average power ratio (PAPR) reduction in Orthogonal Frequency Division Multiplexing (OFDM) systems, radio map reconstruction, beam forming, localization, and interference reduction. We show that they can greatly benefit from the parallel architecture of GPUs.

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Keywords:
Artificial Intelligence and Deep Learning, Autonomous Driving, Robotics, GTC Europe 2018 - ID E8422
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Deep Learning at Twitter's Scale
Cibele Montez Halasz (Twitter)
We'll present Twitter's ML Platform and explain how it allows teams inside the company to run their models in production at Twitter's scale. Machine Learning has allowed Twitter to drive engagement, promote healthier conversations, a ...Read More

We'll present Twitter's ML Platform and explain how it allows teams inside the company to run their models in production at Twitter's scale. Machine Learning has allowed Twitter to drive engagement, promote healthier conversations, and deliver catered advertisements. Over the past year, we have been working on a new chapter of ML at Twitter by migrating our machine learning platform to Tensorflow. This talk will be mainly focusing on this new Machine Learning platform and how we can productionalize our models with it. We will also discuss some of the ways that machine learning is used at Twitter and how we can leverage GPUs to train our models.

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Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8449
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Towards Understanding Deep Neural Network Behaviour
Sebastian Palacio (DFKI)
Interpretability of deep neural networks has focused on the analysis of individual samples. This can distract our attention from patterns originating at the distribution of the dataset itself. We broaden the scope of interpretability analysis, f ...Read More

Interpretability of deep neural networks has focused on the analysis of individual samples. This can distract our attention from patterns originating at the distribution of the dataset itself. We broaden the scope of interpretability analysis, from individual images to entire datasets, and found that some high-performing classifiers use less than half the information contained in any given sample. While the learned features are more intuitive to visualize for image-centric neural networks, in time-series it is much more complicated as there is no direct interpretation of the filters and inputs as compared to image modality. In this talk we are presenting two approaches to analyze the behavior of networks with respect to used input signal, which pave the way to go beyond simple layer stacking and towards a more principled design of neural networks.

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Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8450
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Machine and Deep Learning in Online Marketplaces, FinTech and Video Entertainment
Dmitri Jarnikov (NASPERS)
Naspers is a global internet and entertainment group, and one of the largest technology investors in the world. We currently use machine learning and artificial intelligence for a broad set of purposes, including automation of user interaction (in on ...Read More
Naspers is a global internet and entertainment group, and one of the largest technology investors in the world. We currently use machine learning and artificial intelligence for a broad set of purposes, including automation of user interaction (in online marketplaces), real-time credit scoring (in fintech), user management and churn prediction (in online media) or video segmentation and recommendation (in video entertainment). In this session we will illustrate (1) how deep learning improves user experience in online marketplaces, (2) how we build machine learning models using images and text to create hyper-specialized classifiers for specific market categories and (3) how we use the NVIDIA infrastructure for training these models. The presentation will also share insights on how Naspers sets-up its AI capabilities across a vast network of portfolio companies in 120 locations worldwide, how we share learning across diverse businesses and use cases and how we develop an ecosystem of talent and collaborations.   Back
 
Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8457
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Architecting a Future Proof Data Infrastructure for Your Deep Learning - Presented by NetApp
Hoseb Dermanilian (NetApp), Sally Epstein (Cambridge Consultants)
This session will examine all the factors involved in the architecture of a deep learning pipeline, focusing in on data management and the hybrid cloud approach. It will also highlight the details of a future proof AI infrastructure that can span fro ...Read More
This session will examine all the factors involved in the architecture of a deep learning pipeline, focusing in on data management and the hybrid cloud approach. It will also highlight the details of a future proof AI infrastructure that can span from the edge to the core to the cloud with an enterprise level data management features combined with GPU compute power. Finally, the session will also cover performance and scalability capabilities of such a future proof architecture observed from experimental tests performed in a multi-GPU flash storage based environment.   Back
 
Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8478
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Artificial Intelligence and Deep Learning in Earth Observation
Xiaoxiang Zhu (German Aerospace Center (DLR))
AI is currently penetrating many technological areas. Even though the term is used inflationary today, it often refers to machine learning, usually with deep neural networks (Deep Learning). Internet giants such as Google, Facebook, Microsoft wi ...Read More

AI is currently penetrating many technological areas. Even though the term is used inflationary today, it often refers to machine learning, usually with deep neural networks (Deep Learning). Internet giants such as Google, Facebook, Microsoft with their almost unlimited computing capacities achieved spectacular results in image classification, text translation or in the Go game. At the same time, Earth observation has irreversibly arrived in the Big Data era with the Sentinel satellites (and in the future with Tandem-L). This requires not only new technological approaches to manage large amounts of data, but also new analysis methods. We are one of the pioneers in using Deep Learning in Earth observation and are enthusiastic about its possibilities. Going beyond quick-wins by fine-tuning existing architectures for the usual classification and detection tasks, we take particular care of the fact that Earth observation data and problems are in many aspects different from standard imagery found in the internet. In this talk, a wide spectrum of possibilities where Earth observation could tremendously benefit from methods from AI and Data Science, like deep learning, will be presented.

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Keywords:
Artificial Intelligence and Deep Learning, HPC and Supercomputing, GTC Europe 2018 - ID E8480
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Considerations in Architecting an AI Ready Data Platform
James Coomer (DDN Storage)
Analytics and AI present a serious challenge to businesses in developing new expertise and transforming data architectures from enterprise-class to AI-ready. AI workloads demand a different approach to managing the data lifecycle. The new AI dat ...Read More

Analytics and AI present a serious challenge to businesses in developing new expertise and transforming data architectures from enterprise-class to AI-ready. AI workloads demand a different approach to managing the data lifecycle. The new AI datacenter must be optimized for ingesting, storing, transforming and optimizing data and feeding that data through hyper-intensive analytics workflows and ultimately, extracting value. Ensuring the maximum value of your investment into GPU platforms like NVIDIA's DGX-1 requires careful planning. Learn how to architect and deploy data platforms with robust and balanced performance for all I/O patterns.

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Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8489
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Path to future AI, scenarios & laws: Presented by HPE
Sorin Cheran (HPE)
AI has proceeded over the last 50 years in fits and starts and today the momentum has once again picked up dramatically. New discoveries and techniques in Deep Learning, the best performing AI, are emerging at a rate of one every two months. If ...Read More

AI has proceeded over the last 50 years in fits and starts and today the momentum has once again picked up dramatically. New discoveries and techniques in Deep Learning, the best performing AI, are emerging at a rate of one every two months. If anything, this pace is likely to accelerate in the future as this becomes relevant across many industries. While we are all worried about how to faster accelerate our own workloads, we need to also start thinking about what will come in 10 or 50 years' time. Will we be building an AI beneficial for all or for just some? Are we sure that we are putting the right goals into our AI systems? Shouldn't we make sure that the goals of a General AI are aligned with ours? What are the possible scenarios looking ahead? Let's take an objective look and discuss.

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Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8490
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Artificial Intelligence: how to accelerate your business projects - Presented by ATOS
Cedric Bourrasset (ATOS), Jerome Stoller (Atos)
For your business projects you want to rely on solid partners to master their development and deployment. How to avoid the nightmare of cost increase or exceeding deadlines? How to benefit from industrialized solutions, avoiding demos that have ...Read More

For your business projects you want to rely on solid partners to master their development and deployment. How to avoid the nightmare of cost increase or exceeding deadlines? How to benefit from industrialized solutions, avoiding demos that have been freshly issued from labs?
In this session, you will learn how Atos, with a proven set of products and services, helps you accelerate your projects in HPC, enterprise and Internet of Things domains, from cloud to on-premises, from central to edge while leveraging the most powerful NVIDIA technologies.
Because AI applications and models rely on secure, reliable and up-to-date data, this session will also introduce how Atos is managing, updating and securing data and will end up with a presentation of operational applications in the domains of image recognition, video intelligence, prescriptive maintenance and cyber security.

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Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8492
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Mixed Precision Training of Neural Networks
Carl Case (NVIDIA)
Mixed precision training of deep neural networks provides tremendous benefits: it requires half the storage and data movement of single-precision values, and starting with the Volta GPU's Tensor Cores, provides up to 120 TFLOPS of math throu ...Read More

Mixed precision training of deep neural networks provides tremendous benefits: it requires half the storage and data movement of single-precision values, and starting with the Volta GPU's Tensor Cores, provides up to 120 TFLOPS of math throughput, an 8x speedup over FP32. In this talk, we first present the considerations and techniques when training with reduced-precision, including master weights and automatic loss scaling. After, we discuss real-world training in mixed precision with a particular focus on the PyTorch and TensorFlow frameworks.

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Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8494
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Cross-Systems AI Reference Architecture - Presented by IBM
Florin Manaila (IBM)
GPU Deep Learning is the foundation for the fourth industrial revolution driven by AI. During this session will be presented the IBM AC922 system architecture and design for AI workloads - a fundamental block for Distributed Deep Learning Architectur ...Read More
GPU Deep Learning is the foundation for the fourth industrial revolution driven by AI. During this session will be presented the IBM AC922 system architecture and design for AI workloads - a fundamental block for Distributed Deep Learning Architecture. Various performance aspects will be presented together with related PowerAI software unique market features  Back
 
Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8507
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AI in Telecoms, NVIDIA Platform and Ecosystem
Deepu Talla (NVIDIA), Soma Velayutham (NVIDIA), Manish Harsh (NVIDIA)
Join us for an overview on NVIDIA`s initiatives in Telecommunications Industry. Special update on AI at the edge and its value proposition for 5G and Autonomous Machines. Learn how to leverage NVIDIA developers assets and tools for Telecoms ecosystem ...Read More
Join us for an overview on NVIDIA`s initiatives in Telecommunications Industry. Special update on AI at the edge and its value proposition for 5G and Autonomous Machines. Learn how to leverage NVIDIA developers assets and tools for Telecoms ecosystem.   Back
 
Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8508
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Enterprise AI Your Way: Imagination Is The Limit - Presented by IBM
Carmen Recio (IBM), Alex Hudak (IBM), Florin Manaila (IBM), Charlie Dawson (IMSCAD), Joris Poort (Rescale), Jerry Gutierrez (IBM Cloud), Dilek Sezguen (IBM), Daniel Reiberg (IBM)
IBM Developer Day (Includes 6 sessions) Agenda:
11:00 - General Welcome (Host: Dilek Sezgün) 11.15 - #AI4Good on PowerAI: How can your coding skills help others? (Hackathon) Speaker: Carmen Recio ...Read More

IBM Developer Day (Includes 6 sessions)

Agenda:
11:00 - General Welcome (Host: Dilek Sezgün)

11.15 - #AI4Good on PowerAI: How can your coding skills help others? (Hackathon) Speaker: Carmen Recio

12:00 - Watson-Studio: Putting AI to Work for Business: Umit Mert Cakmak

13:00 - Virtualization is real: Cloud-enabled CAD (Cloud session) Speaker:Alex Hudak, Charlie Dawson (IMSCAD)

14:00 - Integrated IBM AI session (Systems & Cloud) Speaker: Florin Manaila, Alex Hudak

15:00 - Fuel Pipeline for AI (Storage Session),Daniel Reiberg

16:00 - Accelerate and Scale High Performance Computing with IBM Cloud and Rescale, Speaker: Jerry Gutierrez, IBM & Joris Poort, Rescale

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Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8512
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Cross-model Deep Generative Models for Discriminative Tasks: A Sample-efficient Perspective
Frederic Pahde (SAP)
The proposed work deals with learning how to alleviate the information gap in few-shot classification scenarios, i.e. learning new concepts from only few samples. This is facilitated by employing multimodality. For many real world problems, labeled t ...Read More
The proposed work deals with learning how to alleviate the information gap in few-shot classification scenarios, i.e. learning new concepts from only few samples. This is facilitated by employing multimodality. For many real world problems, labeled training data is a scarce resource as it is often very expensive or even impossible to obtain. This makes few-shot learning an attractive research field. We demonstrate a method built upon the idea of cross-modal data generation (text-to-image) in order to mitigate the data sparsity problem. Specifically, we present a meta-learning approach that learns a cross-modal generative adversarial network on base classes (with many samples available) that can be employed for novel classes (with only few samples available) to artificially expand the training set. However, in order to learn a powerful text-to-image mapping an intensive training on base classes is required which necessitates high performance GPU-accelerated hardware to overcome computational issues.  Back
 
Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8514
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Top 5 Lessons Learned Deploying AI in The Real World
Lee Razo (Pure storage)
At Pure Storage, we have helped deploy a number of AI systems including one of the world's fastest supercomputers dedicated to AI and many of the world's most recognized brands in autonomous cars. During our session, Lee Razo, a data tec ...Read More

At Pure Storage, we have helped deploy a number of AI systems including one of the world's fastest supercomputers dedicated to AI and many of the world's most recognized brands in autonomous cars. During our session, Lee Razo, a data technology specialist at Pure Storage will be sharing what we've learned in working with these customers.

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Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8516
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Go from possible to Ready - Dell EMC is simplifying AI for manufacturing - Presented by Dell
Paul Brook (DELL EMC), Thorsten Wujek (it-RSC GmbH)
Learn how organizations around the world are unlocking the value of their data capital with powerful A.I. solutions from Dell EMC. See how our pre-validated Ready Solutions for A.I. make it easy to adopt enterprise grade, highly scalable A.I. infrast ...Read More
Learn how organizations around the world are unlocking the value of their data capital with powerful A.I. solutions from Dell EMC. See how our pre-validated Ready Solutions for A.I. make it easy to adopt enterprise grade, highly scalable A.I. infrastructure, all built using industry leading technologies. During this session, together with our partner IT-RSC, we will demonstrate how we bring Factory 4.0 expertise to bear to deliver turnkey, A.I.-powered predictive maintenance and predictive failure solutions to manufacturers.  Back
 
Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8488
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Deploying and Benchmarking Real-World AI Infrastructure Presented by Pure Storage
Patrick Smith (Pure Storage)
This session examines the full pipeline and infrastructure needed for production Deep Learning, including ingest, data processing and preparation, and storage. We first present a reference data pipeline for AI and explain the role of each stage: ...Read More

This session examines the full pipeline and infrastructure needed for production Deep Learning, including ingest, data processing and preparation, and storage. We first present a reference data pipeline for AI and explain the role of each stage: ingest, inference, ETL, experimentation, and training. The needs for each stage dictate infrastructure decisions: shared storage, mixed compute servers, and a single unified network.
Second, we present a set of benchmarks that run multi-node training on Imagenet that include realistic IO from persistent storage to the CPU and GPU. For this training, we utilize four DGX-1 servers, a single FlashBlade shared storage tier, and an ethernet-only network. Our key result is that we achieve linear scalability of training performance up to 32 GPUs by utilizing FlashBlade, RDMA over Ethernet, and Horovod for multi-GPU scheduling.

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Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8266
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Training Models in TensorFlow with Oversubscribed GPU Memory and NVLink 2.0 - Presented by IBM
Samuel Matzek (IBM)
We will explore what is possible with the unique combination of a model graph that swaps tensors between Volta GPUs and system memory using NVLink 2.0 connections between the GPUs and the system cores. GPU memory size limits the size of models, image ...Read More
We will explore what is possible with the unique combination of a model graph that swaps tensors between Volta GPUs and system memory using NVLink 2.0 connections between the GPUs and the system cores. GPU memory size limits the size of models, image resolution, and batch sizes allowed for neural network training. By combining a graph modification library that adds tensor swap-in / swap-out operations to the graph with NVLink 2.0 connections to the system cores and their memory, we can quickly train with models, image resolutions, and batch sizes that were previously impossible. We will review the graph modification module, the system architecture, and the performance results with standard benchmarks and other models.  Back
 
Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8336
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Edge-Cloud Converged System for Machine Inference and Machine Learning - Presented by Nutanix
Satyam Vaghani (Nutanix)
Edge computing and IoT use cases have inspired machine inference based software stacks on the end and deep learning stacks in the cloud. However, challenges remain. The edge software stack and underlying systems configuration tends to be simplis ...Read More

Edge computing and IoT use cases have inspired machine inference based software stacks on the end and deep learning stacks in the cloud. However, challenges remain. The edge software stack and underlying systems configuration tends to be simplistic against a growing need to enable a richer set of edge applications in a multi-tenant format. The edge and cloud ends are typically developed in a disjoint manner in terms of services offered to the end user. And the workload provisioning frameworks at the edge and in the cloud make it such that ML hardware capabilities are leveraged inefficiently for the purposes of the application. This talk will describe a, edge-to-cloud application runtime, and a "ML hypervisor" to efficiently create applications that span the edge and the cloud and to efficiently map their needs to the underlying hardware's full capabilities.

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Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8479
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GPU Accelerated Data Science
Joshua Patterson (NVIDIA)
In this session, we will explore the latest work, showcase benchmarks, and provide demos of the GPU Open Analytics Initiative (GoAi), a collection of open-source libraries, frameworks, and APIs established to standardize GPU analytics to allow f ...Read More

In this session, we will explore the latest work, showcase benchmarks, and provide demos of the GPU Open Analytics Initiative (GoAi), a collection of open-source libraries, frameworks, and APIs established to standardize GPU analytics to allow for easier development and enhanced performance for GPU-accelerated analytics technologies. Numerous Fortune 500 customers experience latency and performance issues in their data pipeline. Big data frameworks and solutions tried to address this problem, but the cost to scale to the volume and velocity of current needs has proven to be prohibitively expensive. GoAi is addressing these challenges with a vision is to create an end-to-end GPU-accelerated data pipeline that will smooth onboarding ramp for enterprises to explore and integrate AI into their core data driven decision making processes. The session will also provide examples of how customers are benefiting from early primitives and outperforming CPU equivalents.

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Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8495
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World Models and AIs That Invent Their Own Goals
Since 2009, our deep learning artificial neural networks have won numerous contests in pattern recognition and machine learning. Today, they are used billions of times per day by the world's most valuable public companies. True AI, however g ...Read More

Since 2009, our deep learning artificial neural networks have won numerous contests in pattern recognition and machine learning. Today, they are used billions of times per day by the world's most valuable public companies. True AI, however goes far beyond slavishly imitating teachers through deep learning. That's why we have also focused, since 1990, on unsupervised AIs that invent their own goals and experiments to figure out how the world works and what can be done in it. Many of them model the world through a recurrent neural network that learns to predict the consequences of their action sequences. Without a teacher, they derive rewards from continually creating and solving their own, new, previously unsolvable problems, a bit like playing kids do, to become more and more like general problem solvers in the process. Relevant buzzwords include "artificial curiosity" (since 1990) and PowerPlay (since 2011). I will also briefly outline how AIs that set their own goals will eventually colonise the entire universe and make it intelligent.

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Keywords:
Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8140
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Autonomous Driving
Presentation
Media
Software Development for AI, Active Safety and Autonomous Driving Technology - Challenges and Approaches to Make It Real
Erik Coelingh (Zenuity)
This presentation will describe how Zenuity works with deep learning and NVIDIA to simultaneously assure safety as well as enable agile software development.
This presentation will describe how Zenuity works with deep learning and NVIDIA to simultaneously assure safety as well as enable agile software development.  Back
 
Keywords:
Autonomous Driving, GTC Europe 2018 - ID E8141
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Roborace: A Case Study in Collaboration
Bryn Balcombe (Roborace), Johannes Betz (Technical University of Munich)
Roborace Chief Strategy Officer Bryn Balcombe and the Technical University of Munich discuss their collaboration on a pilot project which has given TUM the opportunity to use the Roborace platform to test and develop their autonomous software. T ...Read More

Roborace Chief Strategy Officer Bryn Balcombe and the Technical University of Munich discuss their collaboration on a pilot project which has given TUM the opportunity to use the Roborace platform to test and develop their autonomous software. TUM have had access to Roborace's simulated and real environments, in order to help progress their self driving algorithms with the goal of being able to run one of Roborace's DevBot vehicles at the Formula E event in Berlin. The talk will discuss how the collaboration works, the successes and learnings, and how the platform will be available for more organisations to use in the future.

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Keywords:
Autonomous Driving, GTC Europe 2018 - ID E8306
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Driving Telematics Analytics to Extreme Scale and Interactive Speed
Aaron Williams (OmniSci)
According to a major car manufacturer, modern vehicles are collecting and sharing more than 25 gigabytes of data per hour, from dozens of sensors focused inside and outside the car. Compound that rate of collection across the growing fleets of c ...Read More

According to a major car manufacturer, modern vehicles are collecting and sharing more than 25 gigabytes of data per hour, from dozens of sensors focused inside and outside the car. Compound that rate of collection across the growing fleets of connected vehicles, and the automotive industry is facing a stiff new challenge: making hundreds of billions of location-intelligent data points comprehensible, actionable, and predictive. GPUs running OmniSci's extreme analytics platform are uniquely capable of solving this problem, with orders-of-magnitude faster SQL queries, and full-fidelity rendering on the GPU. In this talk, Aaron Williams will use a real-world example to share best practices for analyzing a large dataset of driving behavior, to lower risk and cultivate better drivers.

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Keywords:
Autonomous Driving, HPC and Supercomputing, GTC Europe 2018 - ID E8348
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Autonomous Buses in City Public Transport
Burak Onur (Temsa Ula??m Araçlar? Sanayi ve Ticaret A.S.), Ali Ufuk Peker (Infotech Bilisim ve ?letisim Teknolojileri A.S.), Tankut Acarman (University of Galatasaray)
Electric City Buses are replacing ICE based transportation in cities. In order to increase the safety of City Traffic we, as Temsa, are working on an autonomous level 4 bus carrying 26 seated and 30 standing passengers with a length of 9.3meters. For ...Read More
Electric City Buses are replacing ICE based transportation in cities. In order to increase the safety of City Traffic we, as Temsa, are working on an autonomous level 4 bus carrying 26 seated and 30 standing passengers with a length of 9.3meters. For the first stage of full autonomous bus we plan to use this bus in university campuses. Basically the bus will stop on determined bus stops, exchange passengers and takes the necessary precautions to stop the bus in case an obstacle is detected by LIDARs and Cameras.  Back
 
Keywords:
Autonomous Driving, GTC Europe 2018 - ID E8440
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Development of a Fail-Operational Autonomous Vehicle for Mobility Challenges
Daniel Watzenig (Virtual Vehicle / TU Graz), Rolf Gramenske (Paravan GmbH)
Automated vehicle technology has the potential to be a game changer on the roads, altering the face of transport and mobility as we experience it by today. Many benefits are expected ranging from improved road safety, increased comfort, reduced conge ...Read More
Automated vehicle technology has the potential to be a game changer on the roads, altering the face of transport and mobility as we experience it by today. Many benefits are expected ranging from improved road safety, increased comfort, reduced congestion, better road utilization, and social inclusion. Enabling mobility - in particular for handicapped and elderly people - is one of the great opportunities enabled by vehicle automation. To move automated vehicles from research prototypes to market entrance, both car manufacturers and suppliers depend on enabling fail-operational electronic technologies for surround sensing, sensor fusion, communications, high-performance processing, by-wire-actuation, and other functions. Ultimately, automated vehicle have to exhibit reliability, robustness, fault-tolerance, and functional safety for any driving scenario, in any weather condition at any time based on a quantified residual risk.  Back
 
Keywords:
Autonomous Driving, GTC Europe 2018 - ID E8447
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Continental's Next Generation AV Systems
Christian Schumacher (Continental BU Advanced Driver Assistance Systems)
Continental is partnering with NVIDIA to provide a complementary solution for the Automotive AV market. We are jointly working on some of the mayor OEM opportunities. The session will provide an overview on Conti´s AV products with ...Read More

Continental is partnering with NVIDIA to provide a complementary solution for the Automotive AV market. We are jointly working on some of the mayor OEM opportunities. The session will provide an overview on Conti´s AV products with infused NVIDIA performance and will give an outlook on future SD challenges to tackle â such as for example simulation and validation.

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Keywords:
Autonomous Driving, GTC Europe 2018 - ID E8453
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Potential of High Performance ECUs in Commercial Vehicle and Off Highway Applications
Mark Mohr (ZF)
Leverage Drive IX for Autonomous Driving in Trucks, Terminal Yard Tractors, excluding passenger cars.
Leverage Drive IX for Autonomous Driving in Trucks, Terminal Yard Tractors, excluding passenger cars.  Back
 
Keywords:
Autonomous Driving, GTC Europe 2018 - ID E8464
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AI and HPC will revolutionize the Automotive industry.
Florian Netter (AUDI AID - Autonomous Intelligent Driving), Marco Fischer (Robotron Datenbank-Software GmbH), Eduard Saller (BMW Group), Asghar Ghorbani (Volkswagen AG), Zach Izham (VW Group)
AI is revolutionizing the $10T transportation industry. Every vehicle will be autonomous â cars, trucks, taxis, buses and shuttles. AI is core to enabling autonomous driving, but AI is also being applied to mobility, logistics, connected vehi ...Read More
AI is revolutionizing the $10T transportation industry. Every vehicle will be autonomous â cars, trucks, taxis, buses and shuttles. AI is core to enabling autonomous driving, but AI is also being applied to mobility, logistics, connected vehicles, connected factory, customer experience and a myriad of other use cases in Automotive. Come learn from experts at Audi, BMW and VW about how they are applying data ingestion, labeling, discovery and exploration to develop trained AI models with significant reductions in the time it takes due to GPU-accelerated computing infrastructures.  Back
 
Keywords:
Autonomous Driving, GTC Europe 2018 - ID E8468
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AI in HD mapping.
William Raveane (Navinfo Europe), Bahram Yoosefizonooz (Navinfo Europe), Willem Strijbosch (TomTom), Ralf Herrtwich (HERE)
By now the industry agrees that HD maps are needed for autonomous driving. Cars need to position themselves very accurately and be aware of the road ahead in order to plan their next move. In this panel session on HD mapping, three map companies will ...Read More
By now the industry agrees that HD maps are needed for autonomous driving. Cars need to position themselves very accurately and be aware of the road ahead in order to plan their next move. In this panel session on HD mapping, three map companies will talk about how they are building HD maps in different regions of the world and how to automate map making using AI. But even more important, how will they keep their HD maps up to date? After all, an out of date HD map will not help the car. The panel will also touch on how cars should access the latest, most up-to-date HD maps with minimal latency.   Back
 
Keywords:
Autonomous Driving, GTC Europe 2018 - ID E8469
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In-cabin Monitoring: Technologies, challenges & roadmap.
Refael Shamir (Letos), Marcos Nieto (Vicomtech), Henrik Lind (Smart Eye AB)
Autonomous Vehicles are transforming automotive industry and how humans interact with these intelligent machines. While we transition from traditional driving to autonomous, in-cabin monitoring becomes key to ensure passengers' safety, atten ...Read More

Autonomous Vehicles are transforming automotive industry and how humans interact with these intelligent machines. While we transition from traditional driving to autonomous, in-cabin monitoring becomes key to ensure passengers' safety, attention and comfort.
The opportunities in this area are huge, ranging from HMI/UX using NLP/Lip reading to co-pilot, eye tracking and monitoring of emotional reactions of the passengers using vision, voice, bio-feedback, sentiment analysis, etc.
This panel will explore the current challenges and opportunities of in-cabin monitoring and the role of AI in this area.

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Keywords:
Autonomous Driving, GTC Europe 2018 - ID E8470
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AI in the Automotive industry with NVIDIA Drive AD Platform.
Murat Durus (NVIDIA), Adi Sahar (NVIDIA), Aaraadhya Narra (NVIDIA), Rohit Taneja (NVIDIA)
The rise of AI has the effect as big as the rise of computers. Autonomous driving is a super-computing problem and latest advances in AI and GPU based computing has enabled the development and acceleration in the self-driving vehicle space where ...Read More

The rise of AI has the effect as big as the rise of computers. Autonomous driving is a super-computing problem and latest advances in AI and GPU based computing has enabled the development and acceleration in the self-driving vehicle space where NVIDIA is fundamentally changing and shaping the future. Furthermore latest advances of the machine learning and neural network based algorithms as well as sensor technology will shape the design of the future car and the evolution of transportation. Artificial intelligence algorithms, intelligent maps and simulation are the main components of the solution to the complex environments and dynamic driving conditions of the autonomous driving problem. There is no way for engineers to hard-code and test every possible variable or situation a car may face in a daily drive and test it on the road. This talk will provide technical insights to the NVIDIA Drive Platform for autonomous vehicle development and its applications in self-driving car space.
This panel will explore the current challenges and developments of AI tied specifically to automotive â how is AI being used to develop autonomous vehicles to revolutionize the transportation and mobility.

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Keywords:
Autonomous Driving, GTC Europe 2018 - ID E8471
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Innovative simulation techniques in the Automotive Industry.
Martin Herrmann (IPG Automotive GmbH), Mike Phillips (Siemens Industries Software and Services B.V.), Jordan Gorrochotegui (Siemens Industry Software and Services B.V.), Rodolphe Tchalekian (ESI GmbH)
This session will explore challenges and innovative approaches to simulation techniques for the development and validation of autonomous vehicles. Panelists will present and discuss opportunities to realistically simulate sensor properties and d ...Read More

This session will explore challenges and innovative approaches to simulation techniques for the development and validation of autonomous vehicles. Panelists will present and discuss opportunities to realistically simulate sensor properties and data, to generate content and how to integrate with NVIDIA's DRIVE ecosystem in a closed-loop environment to combine real driving scenarios with simulation. \n

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Keywords:
Autonomous Driving, GTC Europe 2018 - ID E8472
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Deep Learning software applications for Autonomous Vehicles.
Julian Bock (Institut für Kraftfahrzeuge der RWTH Aachen), Robert Krajewski (Institute for Automotive Engineering of RWTH Aachen University), Bernard Nessler (Institute of Bioinformatics Johannes Kepler University), Ilja Radusch (Fraunhofer FOKUS), Markus Hofmarcher (Institute of Bioinformatics Johannes Kepler University)
This session will discuss how Deep Learning is applied to improve real-time video data analysis for autonomous vehicles, in particular, semantic segmentation. The results of two pilot projects that tested both autonomous and connected drive will ...Read More

This session will discuss how Deep Learning is applied to improve real-time video data analysis for autonomous vehicles, in particular, semantic segmentation. The results of two pilot projects that tested both autonomous and connected drive will be presented as well as the intelligent connected infrastructure required for full Autonomous Driving.

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Keywords:
Autonomous Driving, GTC Europe 2018 - ID E8473
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Deployment of Autonomous Driving Public Transport in Cities
Autonomous driving space is getting crowded these days. With over 50 companies doing public road tests in California and other parts of the world, getting one more self-driving car out there is not overly exciting any longer. Deployments - and b ...Read More

Autonomous driving space is getting crowded these days. With over 50 companies doing public road tests in California and other parts of the world, getting one more self-driving car out there is not overly exciting any longer. Deployments - and by deployments we mean launch of a service powered by self-driving cars - is entirely different story.

During our session we will study the case of launching a public transportation service in a small Russian city powered by Yandex Taxi self-driving car. We're planning to discuss technical aspects of launching the service and specific engineering challenges we faced. We will also update the audience on the state of Yandex autonomous driving technology enabling the service and on our plans for the ongoing development.

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Keywords:
Autonomous Driving, GTC Europe 2018 - ID E8475
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ADAS in Sports Cars
Juergen Bortolazzi (Porsche AG)
Porsche's view on ADAS, with a focus on the specific profile that Porsche sees for sports cars. Porsche's experience with advanced systems like Innodrive as well as topics like the demands on V&V and data driven development. ...Read More

Porsche's view on ADAS, with a focus on the specific profile that Porsche sees for sports cars. Porsche's experience with advanced systems like Innodrive as well as topics like the demands on V&V and data driven development.

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Keywords:
Autonomous Driving, GTC Europe 2018 - ID E8486
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Commercial Vehicle Automation
Robert Falck (EinRide), Stefan Teuchert (MAN Truck & Bus AG), Mark Mohr (ZF)
While we are still at the nascent phase of the Intelligent Industrial Revolution, one industry already started its mutation â transportation. From heavy trucks to shuttles, everything that moves will one day become autonomous. Companies ar ...Read More

While we are still at the nascent phase of the Intelligent Industrial Revolution, one industry already started its mutation â transportation. From heavy trucks to shuttles, everything that moves will one day become autonomous. Companies around the world are exploring AI-led technologies to enable new applications and business models.

This panel will explore the current challenges and opportunities of AI tied specifically to Commercial Vehicles."

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Keywords:
Autonomous Driving, GTC Europe 2018 - ID E8487
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Building Europe's Answer to US and Chinese Hegemony in AVs
Stan Boland (Five AI Inc)
This talk will be an opportunity to explain what challenges exist with introducing autonomous vehicles in Europe, how we are addressing them, what the progress in each field looks like, how we think services will be launched, and what remains to ...Read More

This talk will be an opportunity to explain what challenges exist with introducing autonomous vehicles in Europe, how we are addressing them, what the progress in each field looks like, how we think services will be launched, and what remains to be done (which is a lot). We will include examples of how we are using NVIDIA technology to help us work on problems, show how we've configured our hardware, and discuss how we expect that to evolve from one platform to the next. Tech companies are set to deliver safe AVs ahead of OEMs and tier vendors, but no one has a safe solution for our complex cities or European cities that are more complex than either the US or China. Five AI is Europe's fastest-growing tech company, with just under 100 people from 15 a year ago, created to deliver self-driving technology to Europe's city dwellers.

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Keywords:
Autonomous Driving, Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8152
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Industry Grade Deep Learning & AI Infrastructure for Autonomous Driving
In this talk, we'll discuss Project MagLev, NVIDIA's internal end-to-end AI platform that enables the development of NVIDIA's self-driving car software, DRIVE. We'll explore the platform that supports continuous data ingest from ...Read More

In this talk, we'll discuss Project MagLev, NVIDIA's internal end-to-end AI platform that enables the development of NVIDIA's self-driving car software, DRIVE. We'll explore the platform that supports continuous data ingest from multiple cars (each producing TBs of data per hour) and enables autonomous AI designers to iterate training new neural network designs across thousands of GPU systems and validate their behavior over multi PB-scale data sets. We will talk about our overall architecture, from data center deployment to AI pipeline automation, large-scale AI dataset management, AI training & testing.

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Keywords:
Autonomous Driving, Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8172
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Facing the Challenges of Development and Homologation of Autonomous Driving Using Virtual Approaches
Tobias Dueser (AVL List GmbH), Bernard Schick (University of Applied Science Kempten), Houssem Abdellatif (TÜV SÜD)
Digital Homologation with Simulation for R&D and validation using Nvidia GPU in cloud and HIL.
Securing and homologating automated driving functions presents a huge challenge for market introduction due to an enormous number of scenar ...Read More

Digital Homologation with Simulation for R&D and validation using Nvidia GPU in cloud and HIL.
Securing and homologating automated driving functions presents a huge challenge for market introduction due to an enormous number of scenarios and environment parameter combinations. Confronting conventional real world tests with the new challenges of automated driving is not feasible anymore, and yields to a virtualisation of the testing methods by means of X-in-the-Loop approaches. Especially when using Deep Learning Algorithms for automated driving functions, a scalable, powerful and consistent toolchain is required. Together with TÃV SÃD and the University of Applied Sciences in Kempten, AVL is working on such a consistent toolchain. Different configurations for the development and also approaches for the homologation shall be introduced. Especially the challenge of close-loop-testing, including the vehicle and powertrain dynamics, should be addressed. The challenge is to provide a modular framework integrating existing tools and platforms like NVIDIA's DRIVE platform or NVIDIA's DRIVE SIM to increase the efficiency during development and homologation.

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Keywords:
Autonomous Driving, Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8438
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IBM Storage Reference Architecture for AI applied to Autonomous Driving
Advanced driver assistance systems (ADAS/autonomous driving) are becoming part of all vehicles. All major OEM and Tier-1 auto manufacturers are implementing and testing AD facilities. We examine how real-time sensors, big data computing, data st ...Read More

Advanced driver assistance systems (ADAS/autonomous driving) are becoming part of all vehicles. All major OEM and Tier-1 auto manufacturers are implementing and testing AD facilities. We examine how real-time sensors, big data computing, data storage and data archiving are integrated in today's ADAS/AD systems, providing a fascinating case study, best practices for workflow design, testing and development, data storage and archiving, applicable to all industries.

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Keywords:
Autonomous Driving, Artificial Intelligence and Deep Learning, HPC and Supercomputing, GTC Europe 2018 - ID E8526
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The Reinvention of the Car - and How to Consider Safety Aspects for Launching Autonomous Driving
Michael Hafner (Daimler)
Clearly, Autonomous Driving has the unique potential to change the way we think about transportation. The rapid evolution of sensors, artificial intelligence and IT-infrastructure paves the way to a driverless future much faster than many think. ...Read More

Clearly, Autonomous Driving has the unique potential to change the way we think about transportation. The rapid evolution of sensors, artificial intelligence and IT-infrastructure paves the way to a driverless future much faster than many think. Let's have a look at what is out on the streets today and how we approach the fascinating future of Autonomous Driving at Mercedes-Benz. Title: The Reinvention of the Car - How to Consider Safety Aspects for Launching Autonomous Driving Abstract: Clearly, Autonomous Driving has the unique potential to change the way we think about transportation. The rapid evolution of sensors, artificial intelligence and IT-infrastructure paves the way to a driverless future much faster than many think. Let's have a look at what is out on the streets today and how we approach the fascinating future of Autonomous Driving at Mercedes-Benz Starting with short Video CASE @ Daimler (Connected, Autonomous, Shared, Electric) 1. Innovations in series cars: ADAS Update -History of ADAS Systems -Current Level of Automation (Driver Assistance Systems) -Field Validation 2. Why full vehicle automation makes sense: Motives -Reasons for Vehicle Automation 3. Where are we heading to: Technology -Sensor Setup -Use Case -How to understand Sensor Data -How to collect the needed information -Short Demo Drive (Video) -Experience counts (field testing around the world) -Safe System Architecture -ISO 26262 Development for AD -Strong Partners -Outlook

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Keywords:
Autonomous Driving, GTC Europe 2018 - ID E8399
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Autonomous Machines
Presentation
Media
From Detecting Science Targets on Mars to Detecting Defects in Critical Infrastructure with NVIDIA GPU and Jetson Technology
Mark Woods (Scysis)
As developers of deep learning based applications for extreme environments ranging from Robotic Exploration on Mars through to remote inspection of critical assets we face a host of technology challenges and demands. NVIDIA's portfolio of GP ...Read More

As developers of deep learning based applications for extreme environments ranging from Robotic Exploration on Mars through to remote inspection of critical assets we face a host of technology challenges and demands. NVIDIA's portfolio of GPU and embedded platforms allow us to both develop new analytic functions and offer orders of magnitude better performance year on year. Critically we are able to migrate our cloud based analysis to the edge using Jetson. This talk looks at some of our current work for both Mars exploration and commercial inspection services using AI at the edge.

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Keywords:
Autonomous Machines, GTC Europe 2018 - ID E8506
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Defense Systems and AI-based Vision/Graphics Computing: Challenges and Opportunities
Ross Newman (Abaco Systems)
Autonomous capabilities are proliferating within the defence industry, where robust GPU-based graphics and vision solutions are mission-critical. This session provides an overview of current AI research and development within defence agencies, discus ...Read More
Autonomous capabilities are proliferating within the defence industry, where robust GPU-based graphics and vision solutions are mission-critical. This session provides an overview of current AI research and development within defence agencies, discussing the challenges and opportunities in a vital market segment. Specific topics will include exemplary Land, Sea, and Air defence applications that incorporate AI, along with the technical challenges and solutions related to AI-enabled, low-latency automated classification, tracking, sensor fusion and situational awareness in degraded visual environments. Attendees will also gain insights into solutions offered by GPU-based high-performance embedded computers built for military and aerospace applications.  Back
 
Keywords:
Autonomous Machines, Artificial Intelligence and Deep Learning, Graphics Virtualisation, GTC Europe 2018 - ID E8190
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Sense. Reason. Act. Real-time Perception, Navigation, and Manipulation for Robotic Systems
Michael Suppa (Roboception GmbH)
This presentation introduces innovative, highly efficient solutions for robotic perception, navigation and manipulation, all in 3D and real time, relying on the NVIDIA GPU. Designed specifically for robotic applications, Roboception's rc_visa ...Read More
This presentation introduces innovative, highly efficient solutions for robotic perception, navigation and manipulation, all in 3D and real time, relying on the NVIDIA GPU. Designed specifically for robotic applications, Roboception's rc_visard delivers highly robust on-board perception, enabling a more flexible use for any robotic system. The rc_visard uses an on-board NVIDIA GPU for complex algorithms ranging from stereo and visual odometry up to grasp point computation. Opportunities and challenges of this approach are discussed.  Back
 
Keywords:
Autonomous Machines, Robotics, Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8208
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AI Systems in IoT-Scale Deployments with Simple but Secure Data Distribution
Simon Collins (ADLINK Technology)
This session proposes a simple but robust method of data distribution for large-scale IoT deployments. Attendees will learn how to use a peer-peer publish/subscribe messaging technology based on data topics to facilitate collection of initial in-sit ...Read More
This session proposes a simple but robust method of data distribution for large-scale IoT deployments. Attendees will learn how to use a peer-peer publish/subscribe messaging technology based on data topics to facilitate collection of initial in-situ data, distribution of inferencing models, load-sharing between "worker nodes", collation of inferencing results from many nodes to a central "command", and collation of corner-case data to facilitate iterative updates to the trained model.   Back
 
Keywords:
Autonomous Machines, Robotics, Intelligent Video Analytics, GTC Europe 2018 - ID E8307
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Scalability Analysis of Mini-Cluster Jetson TX2 for Training DNN Applied to Healthcare
John Anderson Garcia (Université Côte d'Azur)
To minimize the execution time for training DNN on low power platforms, mapping tasks that fit with computational resources is the key factor. This talk focuses on the importance of data management according to the number of workers and their memory ...Read More
To minimize the execution time for training DNN on low power platforms, mapping tasks that fit with computational resources is the key factor. This talk focuses on the importance of data management according to the number of workers and their memory capacities, for distributed DNN training on Mini-Cluster Jetson TX2 to minimize the execution time by each epoch. We present DiagnoseNET a framework that provides three high-level features: 1-full DNN workflow orchestration into stage pipelining; as data-mining, unsupervised representation learning and supervised learning. 2-resource manager for training parallel and distributed DNN on multi-GPU server or Jetson TX2 Cluster. 3-energy-monitoring tool for workload characterization. As a case study, we have used an Intensive Care Unit (ICU) dataset with an average of 785,801 Inpatients records by year, to build a general purpose inpatient phenotype representation for general applicative medical targets, such as: predict the Major Clinical Category from inpatients features recorded in hospital admission and clinical attention.  Back
 
Keywords:
Autonomous Machines, Robotics, GTC Europe 2018 - ID E8388
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Designing Autonomous Machines is NOT Autonomous
Ashish Parikh (Arrow)
Designing an autonomous machine are about much more than just the AI. Electrical, Mechanical, Connectivity, and Security are just a few of the disciplines where you will require expertise. Not all companies will have complete expertise in all th ...Read More

Designing an autonomous machine are about much more than just the AI. Electrical, Mechanical, Connectivity, and Security are just a few of the disciplines where you will require expertise. Not all companies will have complete expertise in all these areas. In this session, we will provide examples followed by design considerations, strategies and solutions to begin to address these challenges.

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Keywords:
Autonomous Machines, Intelligent Video Analytics, Robotics, GTC Europe 2018 - ID E8522
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Bioinformatics
Presentation
Media
MULTI-X: An Open AI Marketplace for Precision Medicine
Alejandro Frangi (The University of Sheffield)
The MULTI-X platform simplifies the logistical challenges of deploying AI and ML solutions by providing pre-configured environments with ad-hoc scalable computing resources to quickly build, test, share and reproduce scientific applications. Its comp ...Read More
The MULTI-X platform simplifies the logistical challenges of deploying AI and ML solutions by providing pre-configured environments with ad-hoc scalable computing resources to quickly build, test, share and reproduce scientific applications. Its comprehensible modular framework accelerates the development and reduces the burden and cost of implementing AI solutions. The talk will include details of two exemplary deployments in the area of Cardiac Image Analysis, presented together with the outcome of the analysis of 5000 subjects of the UK-Biobank database. Developing and deploying AI solutions for clinical research use cases can be complex, resource intensive, and therefore expensive and challenging to implement for many researchers, groups and healthcare organisations. In the era of Big-Data and the IoT, the most critical problems are related to the secure access and management of large heterogeneous datasets, the deployment of GPU-accelerated massive parallel processing systems, and the setup of development environments encompassing complex ML tools and applications. Two exemplary use cases of the implementation of GPU-enabled AI solutions in the area of Cardiac Image Analysis, both developed and deployed in MULTI-X, will be presented together with the outcome of the analysis of 5000 Subjects of the UK-Biobank database.  Back
 
Keywords:
Bioinformatics, Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8274
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Brain Reading and Writing with Deep Learning: Future of Neurotechnology
Umut Güçlü (Radboud University), Yağmur Güçlütürk (Radboud University)
Learn about the newest advancements in brain reading and neuroprosthetics, made possible by deep learning techniques, experimentation and augmented reality. Brain reading enables us to observe what people are seeing and perceiving just by analysing t ...Read More
Learn about the newest advancements in brain reading and neuroprosthetics, made possible by deep learning techniques, experimentation and augmented reality. Brain reading enables us to observe what people are seeing and perceiving just by analysing their 3D brain scans, recorded while subjects are observing things in an MRI scanner. Brain writing is, to an extent, opposite, performed by direct stimulation of the brain via microelectrode arrays with the aim of inducing percepts. In developing a new generation of cortical neuroprostheses to stimulate the visual cortex, we are now working toward restoring meaningful visual perception in blind people.  Back
 
Keywords:
Bioinformatics, GTC Europe 2018 - ID E8375
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Financial Services
Presentation
Media
How GPUs Speed the Analysis of Real-Time Risk, Fraud Detection, and Trader Surveillance
James Mesney (KInetica)
Find out how financial companies analyse data using NVIDIA GPU-acceleration, impacting real-time risk management, regulatory reporting, fraud detection and cybersecurity, anti-money laundering, and trader surveillance. We will discuss r ...Read More

Find out how financial companies analyse data using NVIDIA GPU-acceleration, impacting real-time risk management, regulatory reporting, fraud detection and cybersecurity, anti-money laundering, and trader surveillance.

We will discuss real-world examples, including how a specific multinational bank uses a real-time risk management engine running on GPU cloud instances. The bank's analysts can now make time-sensitive, computation-intensive risk calculations involving hundreds of variables, using a real-time, interactive dashboard. This produces meaningful, timely, and consistent financial analysis, optimised to maximise profitability and power business in motion.

This approach lends itself to a data-powered business. It allows banks to move applications â such as counterparty risk analysis â from batch overnight processing to streaming and real-time, creating flexible real-time monitoring of extreme data that makes it easy for traders, auditors, and management to take action.

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Keywords:
Financial Services, GTC Europe 2018 - ID E8177
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Attacking Financial Statement Audits with Adversarial Accounting Records
Marco Schreyer (German Research Center for Artificial Intelligence (DFKI)), Timur Sattarov (PricewaterhouseCoopers GmbH WPG)
This session will explore how auditors can be misguided or "fooled" by adversarial accounting records or adversarial financial transactions. Recent discoveries in deep learning research revealed that learned models are vulnera ...Read More

This session will explore how auditors can be misguided or "fooled" by adversarial accounting records or adversarial financial transactions.

Recent discoveries in deep learning research revealed that learned models are vulnerable to "adversarial examples," or a sample of slightly modified input data that intends to cause a human and/or machine to misclassify it. Such examples exhibit the potential to be dangerous, since they could be specifically designed to misguide auditors or an accountant. Securing accounting information systems against such "attacks" can be difficult. In this talk, we'll explain why such "adversarial examples" are of vital relevance in the context of fraud detection and financial statement audits. We will demonstrate how autoencoder neural networks can be trained in an adversarial setup to generate "fake" accounting records or financial transactions. Such financial transactions might be misused to "attack" an organization's internal control system or obfuscate fraudulent activities. The training of such examples was conducted by training several adversarial autoencoders using NVIDIA's DGX-1 system.

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Keywords:
Financial Services, GTC Europe 2018 - ID E8212
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FinGAN - Generating Stock Price Sequences to Simulate Future Market Scenarios
Jacopo Credi (Axyon AI SRL), Matteo Casolari (Axyon AI SRL)
Learn about FinGAN, a conditional generative adversarial network framework for generating realistic financial time-series, providing support for market analysis and investment strategies. We will introduce our conditional sequence-to-sequence GAN arc ...Read More
Learn about FinGAN, a conditional generative adversarial network framework for generating realistic financial time-series, providing support for market analysis and investment strategies. We will introduce our conditional sequence-to-sequence GAN architecture and show how it can be trained, contrary to the theory of random walks in stock market prices. Then, we will show how this model can be used for market directionality and volatility prediction, for performing GPU-powered large-scale simulations of future market scenarios under real or controlled conditions, and for detecting anomalous behaviours in financial markets.  Back
 
Keywords:
Financial Services, GTC Europe 2018 - ID E8323
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Privacy-Preserving Sharing of Financial Transaction Data with Deep Generative Models
Financial transaction data are one of the most privacy sensitive datasets out there, and yet their digital trail of data points result in highly unique fingerprints, making information-retaining anonymization thereof a hard problem. But one, tha ...Read More

Financial transaction data are one of the most privacy sensitive datasets out there, and yet their digital trail of data points result in highly unique fingerprints, making information-retaining anonymization thereof a hard problem. But one, that turns out to be solvable thanks to advances in AI.

For one of the largest retail banks operating in Central East Europe we deployed deep generative models, that train on over half a billion of transactions, in order to then generate highly realistic & representative synthetic customers, matching the patterns of the actual customers. By adapting auto-regressive neural networks to a highly heterogeneous data structure, we learn and thus retain detail, structure as well as variation of your privacy-sensitive data at an unprecedented level, while rendering the re-identification of any individual impossible. As this data can then be utilized without putting the privacy of customers at risk, this enables open collaboration for the development and testing of their digital services.

This type of modeling at that scale would not have been feasible without the advances in generative modeling as well as GPU technology

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Keywords:
Financial Services, GTC Europe 2018 - ID E8377
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Gaming
Presentation
Media
Learning Character Controllers from Motion Capture Data
Taku Komura (University of Edinburgh), Sebastian Starke (The University of Edinburgh)
This session will be about deep learning frameworks that we have developed for interactive character control. The first approach is called a Phase-Functioned Neural Network (PFNN). The entire network is trained in an end-to-end fashion on a larg ...Read More

This session will be about deep learning frameworks that we have developed for interactive character control. The first approach is called a Phase-Functioned Neural Network (PFNN). The entire network is trained in an end-to-end fashion on a large dataset composed of locomotion, such as walking, running, jumping, and climbing movements, fitted into virtual environments. Our system can therefore automatically produce motions where the character adapts to different geometric environments such as walking and running over rough terrain, climbing over large rocks, jumping over obstacles, and crouching under low ceilings. Once trained, our system is also extremely fast and compact, requiring only milliseconds of execution time and a few megabytes of memory, even when trained on gigabytes of motion data.

The second approach is called Mode-Adaptive Neural Networks. This is an extension of the PFNN and has the capability to control quadruped characters, where the locomotion is multimodal. Once trained, the quadruped produce different gait types such as walk, pace, trot, and canter by simply changing the velocity of the character. The frameworks are suitable for computer games and VR.

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Keywords:
Gaming, GTC Europe 2018 - ID E8293
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Super-resolution for aliased images
Artem Rozantsev (NVIDIA), Marco Foco (NVIDIA)
In this talk we discuss different techniques for training the super resolution algorithm with the focus on producing high quality results on the highly aliased and noisy data. Though such artifacts are not often present in the real images, they frequ ...Read More
In this talk we discuss different techniques for training the super resolution algorithm with the focus on producing high quality results on the highly aliased and noisy data. Though such artifacts are not often present in the real images, they frequently appear in gaming and animation images and videos. To solve this problem, we have introduced a special downsampling procedure that allows the network to simultaneously do anti-aliassing, denoising and super-resolution. Our experiments show that even though our model was trained solely on natural images, it is able to achieve significant improvement for aliased and noisy animation images.  Back
 
Keywords:
Gaming, Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8523
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Introduction to real-time Raytracing with NVIDIA RTX
Martin Stich (NVIDIA)
Raytracing is the hallmark feature of NVIDIA's just-released Turing GPU in the GeForce RTX and Quadro RTX series. RTX for the first time brings raytracing to a mass consumer audience â a feat that just a few months ago was considered y ...Read More

Raytracing is the hallmark feature of NVIDIA's just-released Turing GPU in the GeForce RTX and Quadro RTX series. RTX for the first time brings raytracing to a mass consumer audience â a feat that just a few months ago was considered years in the future. This talk by one of the lead engineers on the project will walk you through some core principles of raytracing, give an overview of the RTX technology, and explain how it applies to real-time applications such as games

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Keywords:
Gaming, GTC Europe 2018 - ID E8527
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NVIDIA RTX in Remedy Northlight engine
Juha Sjoholm (NVIDIA)
Remedy Entertainment is one of the first game studios that have started working with NVIDIA RTX technology. The session describes how RTX is used today in the company's in-house game engine, Northlight. Implementations of shadows, reflection ...Read More

Remedy Entertainment is one of the first game studios that have started working with NVIDIA RTX technology. The session describes how RTX is used today in the company's in-house game engine, Northlight. Implementations of shadows, reflections, ambient occlusion and indirect diffuse illumination effects with RTX are explained. Additionally, the session talks about general best practices about how to most efficiently use RTX through Microsoft DXR API in a game engine.

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Keywords:
Gaming, GTC Europe 2018 - ID E8530
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Genomics
Presentation
Media
Genomes and GPUs: How Biology is Harnessing Electronics to Bring DNA Information to Anyone, Anywhere
Rosemary Dokos (Oxford Nanopore Technologies Ltd), Leila Luheshi (ONT)
Oxford Nanopore has built the first and only real-time, portable DNA sequencer - the MinION. It is being used to bring DNA information to researchers in many sectors, including biomedical/cancer research, environmental monitoring, agriculture, f ...Read More

Oxford Nanopore has built the first and only real-time, portable DNA sequencer - the MinION. It is being used to bring DNA information to researchers in many sectors, including biomedical/cancer research, environmental monitoring, agriculture, food/ water testing, and education. Oxford Nanopore is using GPUs to make sure that genomic data can be processed in real time, delivering potential benefits of rapid insights to users in any environment. Leila Luheshi and Rosemary Dokos will talk about current and potential healthcare applications of Nanopore technology, and how GPUs will turn sequence data into rapid insights for disease or environmental management.

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Keywords:
Genomics, Bioinformatics, GTC Europe 2018 - ID E8179
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Graphics Virtualisation
Presentation
Media
BIM Cloud Workspace on Azure, Citrix and NVIDIA GRID
Jeroen Pat (TBI), Frank Wolbertus (TBI)
GPU virtualisation in the Cloud has ushered in a new era for architects, builders, designers and engineers. In this case study session you will learn how TBI personnel are now using BIM applications including BIM 360, Solibri, Revit and Navisworks, t ...Read More
GPU virtualisation in the Cloud has ushered in a new era for architects, builders, designers and engineers. In this case study session you will learn how TBI personnel are now using BIM applications including BIM 360, Solibri, Revit and Navisworks, through a digital workspace hosted on Citrix XenDesktop HDX 3D Pro running on Microsoft Azure NV-series virtual machines with NVIDIA virtual GPUs, NVIDIA GRID and Tesla M60s. This technology stack enables TBI employees to work together in real time, from any location, while enjoying a highly optimised 3D user experience on any device, even the low-cost Raspberry Pi. In their technology journey, TBI progressed from an age of 2D flatland, to the more advanced age of optimization of 3D digital data, to the present-day era of interoperability and collaboration in a new age where connectivity is key.  Back
 
Keywords:
Graphics Virtualisation, Professional Visualisation, GTC Europe 2018 - ID E8139
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How to Choose a GPU for your Environment with the Game Skyrim
Gemma van der Voorst (University of Groningen)
When talking about GPU benchmarking and making the right choice of GPU for your organisation or workload, you'll probably think of using fancy benchmark tools. But there is a much more fun and low-cost way to do so. This session is about how ...Read More

When talking about GPU benchmarking and making the right choice of GPU for your organisation or workload, you'll probably think of using fancy benchmark tools. But there is a much more fun and low-cost way to do so. This session is about how to benchmark and make a GPU choice with the game Skyrim. It's a very low level way of testing using the NVIDIA-smi on the hypervisor and Powershell in the Windows VDI. Make your own charts with the information you collect yourself. This session is based on Windows 10 VDI, and VMware vSphere 6.7.

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Keywords:
Graphics Virtualisation, GTC Europe 2018 - ID E8155
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Maximize Data Center Resources: How to run VDI, HPC and AI Workloads on Common Infrastructure
Wietze Albers (University of Groningen), Gemma van der Voorst (University of Groningen)
What if you could combine VDI, HPC, Deep Learning and AI all together on one platform with VMware vSphere 6.7 and NVIDIA virtual GPU (vGPU) technology? In this session, we'll guide you through how to set up a uniform, well-performing platform ...Read More
What if you could combine VDI, HPC, Deep Learning and AI all together on one platform with VMware vSphere 6.7 and NVIDIA virtual GPU (vGPU) technology? In this session, we'll guide you through how to set up a uniform, well-performing platform. We will cover the virtualisation of HPC, the sharing of compute resources with VDI, and the implementation of mixed workloads leveraging NVIDIA vGPU technology, and automation of the platform. If you want to have fun at work while preparing for the the future, don't miss this N3RD session!  Back
 
Keywords:
Graphics Virtualisation, GTC Europe 2018 - ID E8156
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Digital Disruption: Enabling BIM Agility in Construction Using NVIDIA Quadro vDWS
Andrew Bowker (ebb3 ltd), Gary Scott (Willmott Dixon - Cobham)
This session will involve a live case study of how the Willmott Dixon and ebb3 partnership are leveraging NVIDIA Quadro Virtual Data Center Workstation (Quadro vDWS) enabled services to support its internal teams and customers as the AEC sector ...Read More

This session will involve a live case study of how the Willmott Dixon and ebb3 partnership are leveraging NVIDIA Quadro Virtual Data Center Workstation (Quadro vDWS) enabled services to support its internal teams and customers as the AEC sector in the UK moves rapidly towards digital transformation. We will explain one of the current problems that exist with BIM and the journey towards Level 3 in the UK, the barriers to users working with federated BIM models, and the ever increasing use of data within an analogue industry.The session will cover a live project visualisation and examples of using it within a collaborative environment to reduce time and costs.

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Keywords:
Graphics Virtualisation, Virtual and Augmented Reality, GTC Europe 2018 - ID E8161
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Learn How the New NVIDIA vGPU Software Helps Deliver the Agile Data Center
John Fanelli (NVIDIA), Anne Hecht (NVIDIA)
With the latest release of NVIDIA vGPU software the world's most powerful virtual workstation gets even more powerful. Learn more about how our latest enhancements enable your data center to be more agile and scale your data center to meet t ...Read More

With the latest release of NVIDIA vGPU software the world's most powerful virtual workstation gets even more powerful. Learn more about how our latest enhancements enable your data center to be more agile and scale your data center to meet the needs of thousands to ten-thousands and even hundreds of thousands of users. The newest release of NVIDIA virtual GPU software adds support for more powerful VMs, which can be managed from the cloud or from the on premises data center, or private cloud. With support for live migration of GPU-enabled VMs, IT can truly deliver high availability and a quality user experience. IT can further ensure they get the most out of their investments with the ability to re-purpose the same infrastructure that runs VDI during the day to run HPC and other compute workloads at night. In this session, we will unveil the new features of NVIDIA vGPU solutions and demonstrate how GPU virtualization enables you to easily support the most demanding users and scale virtualized, digital workspaces on an agile and flexible infrastructure, from the cloud and as well as the on premises data center.

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Keywords:
Graphics Virtualisation, GTC Europe 2018 - ID E8513
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Citrix XenApp / Microsoft RDSH - How to Get the Best User Experience and Performance with NVIDIA vGPU Technology
Jan Hendrik Meier (Grimme Landmaschinenfabrik GmbH & Co. KG), Thomas Remmlinger (NVIDIA)
During this session, attendees will learn about sizing and optimising a Citrix Xenapp / Microsoft RDSH environment with NVIDIA virtual GPU (vGPU) technology. Learn why it is especially important in XenApp environments to keep an eye on the framebuffe ...Read More
During this session, attendees will learn about sizing and optimising a Citrix Xenapp / Microsoft RDSH environment with NVIDIA virtual GPU (vGPU) technology. Learn why it is especially important in XenApp environments to keep an eye on the framebuffer and make sure the load is not too high. Get the best performance out of your environment by using the best architecture and sizing on the basics of a real world scenario with Grimme, the world market leader for potato farming technology. In 2016, Grimme launched a project to replace their existing Citrix XenApp Infrastructure and decided to use NVIDIA Tesla cards and NVIDIA vGPU software in the new environment to improve performance and user experience.  Back
 
Keywords:
Graphics Virtualisation, Professional Visualisation, GTC Europe 2018 - ID E8120
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HPC and Supercomputing
Presentation
Media
AI and HPC as Drivers for Industrial Competitiveness
Alison Kennedy (Hartree Center)
The Hartree Centre, a department of the UK National Labs, focusses on industry-led challenges in HPC, High Performance Data Analytics, and AI. Its mission is to make UK industry more competitive through the uptake of novel technologies. Historic ...Read More

The Hartree Centre, a department of the UK National Labs, focusses on industry-led challenges in HPC, High Performance Data Analytics, and AI. Its mission is to make UK industry more competitive through the uptake of novel technologies. Historically the focus has been on HPC (simulation and modelling), and more recently on data centric computing. This sessions focuses on on how AI can best be applied to add value for industry partners.

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Keywords:
HPC and Supercomputing, GTC Europe 2018 - ID E8105
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GPU-Accelerated Computing at Scale
Dirk Pleiter (Forschungszentrum Jülich)
In pushing the limits of throughput of floating-point operations, GPUs have become a unique technology. During this session, we'll explore the current state of affairs from an application perspective. For this, we'll consider different c ...Read More

In pushing the limits of throughput of floating-point operations, GPUs have become a unique technology. During this session, we'll explore the current state of affairs from an application perspective. For this, we'll consider different computational science areas including fundamental research on matter, materials science, and brain research. Focusing on key application performance characteristics, we review current architectural and technology trends to derive an outlook towards future GPU-accelerated architectures.

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Keywords:
HPC and Supercomputing, GTC Europe 2018 - ID E8108
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Multi GPU Programming Models
Jiri Kraus (NVIDIA)
Do you need to compute larger or faster than a single GPU allows you to? Learn how to scale your application to multiple GPUs. Learn how to use the different available multi-GPU programming models and about their individual advantages. All programmin ...Read More
Do you need to compute larger or faster than a single GPU allows you to? Learn how to scale your application to multiple GPUs. Learn how to use the different available multi-GPU programming models and about their individual advantages. All programming models will be introduced using the example of applying a domain decomposition strategy.  Back
 
Keywords:
HPC and Supercomputing, GTC Europe 2018 - ID E8121
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Accelerating Weather Prediction with OpenACC
Paddy Gillies (European Centre for Medium Range Weather Forecasts (ECMWF)), Alan Gray (NVIDIA)
In this talk attendees will learn how key algorithms for Numerical Weather Prediction were ported to the latest GPU technology and the substantial benefits gained from doing so. We will showcase the power of individual Voltas and the impressive perfo ...Read More
In this talk attendees will learn how key algorithms for Numerical Weather Prediction were ported to the latest GPU technology and the substantial benefits gained from doing so. We will showcase the power of individual Voltas and the impressive performance of the cutting edge DGX-2 server with multiple GPUS connected by a high speed interconnect.  Back
 
Keywords:
HPC and Supercomputing, GTC Europe 2018 - ID E8195
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Extending a Legacy Fortran to Code to GPUs Using OpenACC
Gabriel Staffelbach (CERFACS)
In this session, we will describe how we successfully extended a large legacy fortran code to GPUs using OpenACC. Based on a state of the art code for combustion simulation AVBP (http://www.cerfacs.fr/avbp7x/), our objective is to keep the code as si ...Read More
In this session, we will describe how we successfully extended a large legacy fortran code to GPUs using OpenACC. Based on a state of the art code for combustion simulation AVBP (http://www.cerfacs.fr/avbp7x/), our objective is to keep the code as simple as possible for the AVBP community while taking advantage of high end computing resources as GPU; OpenACC allows the flexibility to conduct the extension with respect to these constraints. This session will present the various strategies we tried during the refactoring of the application, including the limitations of the directive-only approach which can severely impair performance on particular parts of the code. The lessons learned are applicable to a wide range of codes in the research community.   Back
 
Keywords:
HPC and Supercomputing, GTC Europe 2018 - ID E8217
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Efficient Use of GPUs for High Fidelity CFD Simulations
Jesús Pueblas Sánchez-Guerra (ITP Aero)
This session will describe strategies to achieve an efficient implementation of a parallel high fidelity CFD solver that runs on GPUs. The solver is based on a nodal Discontinuous Galerkin Flux Reconstruction spatial discretisation. The strong data l ...Read More
This session will describe strategies to achieve an efficient implementation of a parallel high fidelity CFD solver that runs on GPUs. The solver is based on a nodal Discontinuous Galerkin Flux Reconstruction spatial discretisation. The strong data locality of the resulting scheme makes it very attractive to be implemented on GPUs. Details of the implementation of the most time consuming kernels are provided, putting emphasis on the extensive use of the GPU shared memory to minimize the memory access time penalty. The communications between GPUs also play a big role in the solver parallel performance. The benefits of overlapping communication and computation will also be quantified. The resulting solver is able to perform LES and DNS simulations of low pressure turbines blades within engine design time scales.  Back
 
Keywords:
HPC and Supercomputing, GTC Europe 2018 - ID E8223
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Predicting Atmospheric Turbulence: The Key to Imaging Habitable Planets with Large Telescopes
Olivier Guyon (University of Arizona & Subaru Telescope), Damien GRATADOUR (Observatoire de Paris & Université Paris Diderot)
Come and learn how GPUs help identify biological activity on nearby exoplanets. Deployed on on the Japanese Subaru telescope at 4,200m elevation atop Maunakea, Hawaii, the GPU hardware technology constitutes the backbone of the adaptive optics, which ...Read More
Come and learn how GPUs help identify biological activity on nearby exoplanets. Deployed on on the Japanese Subaru telescope at 4,200m elevation atop Maunakea, Hawaii, the GPU hardware technology constitutes the backbone of the adaptive optics, which drives the real-time correction of the optical aberrations introduced by Earth's atmosphere. Using machine learning technique and advanced linear algebra algorithms accelerated by GPUs, a predictive control problem can now be solved at the multi-kHz frame rate required to keep up with turbulence changes. This represents the first successful on-sky result of this approach for exoplanet imaging.  Back
 
Keywords:
HPC and Supercomputing, GTC Europe 2018 - ID E8251
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The Need for Speed - Towards High-Fidelity CFD Simulations Near Real-Time
Christian F. Janßen (Altair Engineering)
Learn how GPU-based Computational Fluid Dynamics (CFD) paves the way for affordable high-fidelity simulations for simulation-based design. This talk gives insights into the key ingredients of academic and commercial GPU-accelerated CFD solvers and di ...Read More
Learn how GPU-based Computational Fluid Dynamics (CFD) paves the way for affordable high-fidelity simulations for simulation-based design. This talk gives insights into the key ingredients of academic and commercial GPU-accelerated CFD solvers and discusses the technical and physical challenges of (near) real-time simulations of complex flows. Then, ultraFluidX is presented, a recently released commercial GPU-based CFD solver. The solver was specifically designed to leverage the massively parallel architecture of GPUs. With its multi-GPU implementation based on CUDA-aware MPI, the tool can achieve turnaround times of just a few hours for simulations of fully detailed production-level passenger and heavy-duty vehicles. Basics of the solver and several selected application examples are presented.  Back
 
Keywords:
HPC and Supercomputing, GTC Europe 2018 - ID E8253
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CPU/GPU Co-execution with OpenACC: Techniques for Algebraic Assembly in Finite Element Methods
Guillaume Houzeaux (Barcelona Supercomputing Center), Ricard Borrell (Barcelona Supercomputing Center)
We present in this talk a portable matrix assembly strategy used in solving PDEs, suited for co-execution on both the CPUs and accelerators. In addition, a dynamic load balancing strategy is considered to balance the workload among the different ...Read More

We present in this talk a portable matrix assembly strategy used in solving PDEs, suited for co-execution on both the CPUs and accelerators. In addition, a dynamic load balancing strategy is considered to balance the workload among the different CPUs and GPUs available on the cluster. Numerical methods for solving partial differential equations (PDEs) involve two main steps: the assembly of an algebraic system of the form Ax=b and the solution of it with direct or iterative solvers. The assembly step consists of a loop over elements, faces and nodes in the case of the finite element, finite volume, and finite difference methods, respectively. It is computationally intensive and does not involve communication. It is therefore well-suited for accelerators.

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Keywords:
HPC and Supercomputing, GTC Europe 2018 - ID E8292
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OpenStaPLE, an OpenACC Lattice QCD Application
Enrico Calore (University of Ferrara and INFN Ferrara)
This talk provides an overview of the key strategies used to design and implement OpenStaPLE, an application for Lattice QCD (LQCD) Monte Carlo simulations. LQCD are an example of HPC grand challenge applications, where the accuracy of results s ...Read More

This talk provides an overview of the key strategies used to design and implement OpenStaPLE, an application for Lattice QCD (LQCD) Monte Carlo simulations. LQCD are an example of HPC grand challenge applications, where the accuracy of results strongly depends on available computing resources. OpenStaPLE has been developed on top of MPI and OpenACC frameworks. It manages the parallelism across multiple computing nodes and devices, while OpenACC exploits the high level parallelism available on modern processors and accelerators, enabling a good level of portability across different architectures. After an initial overview, we also present performance and portability results on different architectures, highlighting key improvements of hardware and software key that may lead this class of applications to exhibit better performances.

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Keywords:
HPC and Supercomputing, GTC Europe 2018 - ID E8317
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GPU-Accelerated Real Space Electronic Structure Theory on HPC Resources
William Huhn (Duke University), Volker Blum (Duke University)
We present our experiences implementing GPU acceleration in the massively parallel, real space FHI-aims electronic structure code for computational materials science. For fourteen years, FHI-aims has focused on high numerical accuracy for curren ...Read More

We present our experiences implementing GPU acceleration in the massively parallel, real space FHI-aims electronic structure code for computational materials science. For fourteen years, FHI-aims has focused on high numerical accuracy for current methods, such as Kohn-Sham density-functional theory and beyond, and on outstanding scaling on distributed-parallel high-performance computers. We show how to exploit vectorized implementations in FHI-aims to achieve an overall 3x-4x GPU acceleration with minimal code rewrite for complete simulations. Furthermore, FHI-aims' domain decomposition scheme on non-uniform grids enables compute and memory-parallel computing across thousands of GPU-containing nodes for real-space operations.

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Keywords:
HPC and Supercomputing, GTC Europe 2018 - ID E8321
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Porting Quantum ESPRESSO to GPU Accelerated Systems
Pietro Bonfa' (CINECA)
This talk will present the roadmap, the strategy and the currently ongoing efforts to port the fundamental building blocks of the QuantumESPRESSO suite of codes to accelerated architectures. QuantumESPRESSO is an integrated suite of codes provid ...Read More

This talk will present the roadmap, the strategy and the currently ongoing efforts to port the fundamental building blocks of the QuantumESPRESSO suite of codes to accelerated architectures. QuantumESPRESSO is an integrated suite of codes providing computational methods to estimate a vast number of physical properties at the nanoscale. It features high modularity and a user-oriented design, and it can efficiently exploit standalone workstations as well as state-of-art HPC systems. The differences characterizing this new work and the original GPU porting done in CUDA C back in 2012 will be used to discuss aspects of code evolution and maintainability. Special attention will also be devoted to the performance-critical kernels shared by most of the components of the suite.

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Keywords:
HPC and Supercomputing, GTC Europe 2018 - ID E8340
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Porting VASP to GPUs with OpenACC
Stefan Maintz (NVIDIA)
VASP is a software package for atomic-scale materials modeling. It's one of the most widely used codes for electronic-structure calculations and first-principles molecular dynamics. We'll give an overview on the status of porting VASP to ...Read More

VASP is a software package for atomic-scale materials modeling. It's one of the most widely used codes for electronic-structure calculations and first-principles molecular dynamics. We'll give an overview on the status of porting VASP to GPUs with OpenACC. Parts of VASP were previously ported to CUDA C with good speed-ups on GPUs, but also with an increase in the maintenance workload, because VASP is otherwise written wholly in Fortran. We'll discuss OpenACC performance relative to CUDA, the impact of OpenACC on VASP code maintenance, and challenges encountered in the port related to management of aggregate data structures. Finally, we'll discuss possible future solutions for data management that would simplify both new development and the maintenance of VASP and similar large production applications on GPUs.

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Keywords:
HPC and Supercomputing, GTC Europe 2018 - ID E8367
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Using GPUs to Accelerate Online Event Reconstruction at the Large Hadron Collider
Andrea Bocci (CERN)
Today we are investigating different technologies and architectures, and we will present the first hardware and software prototype that will evolve into a system able to overcome an unprecedented challenge. To probe the predictions of t ...Read More

Today we are investigating different technologies and architectures, and we will present the first hardware and software prototype that will evolve into a system able to overcome an unprecedented challenge.

To probe the predictions of the Standard Model of Particle Physics, the Large Hadron Collider at CERN will be upgraded by 2026 to produce 6 billion proton collisions every second at the centre of the Compact Muon Solenoid (CMS) detector. These collisions produce events in which new particles, which did not exist before the collision, are generated.

The CMS experiment will be able to observe and record the most energetic and rare of these events.

Observing the details of all these events requires reading and analyzing almost 100TB of data every second... and CMS is working on a hybrid approach to tackle this challenge: ASICs and FPGAs will be used for the first level of data reduction, while a hybrid cluster of computer servers and GPUs will be used for the full event reconstruction and final online selection.

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Keywords:
HPC and Supercomputing, GTC Europe 2018 - ID E8382
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Interactive Supercomputing at the Crossroads of HPC and Cloud Technologies
Sadaf R. ALAM (Swiss National Supercomputing Centre (CSCS))
This talk would cover the background and distinguishing features of the European Interactive Computing E-Infrastructure (ICEI) project, which will offer a set of federated services to realize the Fenix infrastructure (https://fenix-ri.eu). For decade ...Read More
This talk would cover the background and distinguishing features of the European Interactive Computing E-Infrastructure (ICEI) project, which will offer a set of federated services to realize the Fenix infrastructure (https://fenix-ri.eu). For decades, high "performance" computing, networking, and storage technologies have been among the driving forces behind numerous scientific discoveries and breakthroughs. Recently, the X-as-a-service model offered by several cloud technologies has enabled researchers, particularly in the fields of data science, to access resources and services in an on-demand and elastic manner. Complex workflows in different domains, such as the European Human Brain Project (HBP), however require a converged, consolidated, and flexible set of infrastructure services to support their performance and accessibility requirements.   Back
 
Keywords:
HPC and Supercomputing, Graphics Virtualisation, GTC Europe 2018 - ID E8106
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Simulations Meet Machine Learning in Computational Structural Biology and Drug Discovery
Gianni De Fabritiis (Universitat Pompeu Fabra/Acellera)
Classical molecular dynamics (MD) simulations will be able to reach sampling in the second timescale within five years thanks to GPUs, producing petabytes of simulation data at current force field accuracy. Notwithstanding this, MD will still be in t ...Read More
Classical molecular dynamics (MD) simulations will be able to reach sampling in the second timescale within five years thanks to GPUs, producing petabytes of simulation data at current force field accuracy. Notwithstanding this, MD will still be in the regime of low-throughput, high-latency predictions with average accuracy. We envisage that machine learning (ML) will be able to solve both the accuracy and time-to-prediction problem by learning predictive models using expensive simulation data. The synergies between classical, quantum simulations and ML methods, such as artificial neural networks, have the potential to drastically reshape the way we make predictions in computational structural biology and drug discovery.  Back
 
Keywords:
HPC and Supercomputing, Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8116
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Applications of Deep Learning to Nuclear Fusion Research
Diogo R. Ferreira (IST, University of Lisbon)
Nuclear fusion is the process that powers the sun, and it is one of the best hopes of achieving a virtually unlimited energy source for the future of humanity. However, reproducing sustainable nuclear fusion reactions here on Earth is a tremendous sc ...Read More
Nuclear fusion is the process that powers the sun, and it is one of the best hopes of achieving a virtually unlimited energy source for the future of humanity. However, reproducing sustainable nuclear fusion reactions here on Earth is a tremendous scientific and technical challenge. Special devices - called tokamaks - have been built around the world, with JET (Joint European Torus, in the UK) being the largest tokamak currently in operation. Such devices confine matter and heat it up to extremely high temperatures, creating a plasma where fusion reactions begin to occur. JET has over one hundred diagnostic systems to monitor what happens inside the plasma, and each 30-second experiment generates about 50 GB of data to be analyzed. In this talk, we will show how Convolutional Neural Networks (CNNs) can be used to reconstruct the 2D plasma profile inside the device based on data coming from those diagnostics. We will also discuss how Recurrent Neural Networks (RNNs) can be used to predict plasma disruptions, which are one of the major problems affecting fusion devices today. Training of such networks is done on NVIDIA GPUs.  Back
 
Keywords:
HPC and Supercomputing, Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8144
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GPU Computing in Structural Bioinformatics and its Applications
José María Cecilia Canales (UCAM)
In this talk we will give an overview of the benefits GPU computing can provide to the Structural Bioinformatics field. We will explain how most of biomolecular simulations methods can be efficiently accelerated using massively computational architec ...Read More
In this talk we will give an overview of the benefits GPU computing can provide to the Structural Bioinformatics field. We will explain how most of biomolecular simulations methods can be efficiently accelerated using massively computational architectures and will show several fundamental research and technology transfer success cases.  Back
 
Keywords:
HPC and Supercomputing, Bioinformatics, Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8287
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OpenPOWER Platforms for HPC and AI: French Technology Watch Group Results
Gabriel Hautreux (GENCI)
In 2014, GENCI set up a French technology watch group that targets the provisioning of test systems, selected as part of the prospective approach among partners from GENCI. This was done in order to prepare scientific commun ...Read More

In 2014, GENCI set up a French technology watch group that targets the provisioning of test systems, selected as part of the prospective approach among partners from GENCI. This was done in order to prepare scientific communities and users of GENCI's computing resources for the arrival of the next "Exascale" technologies.\nThe talk will present results obtained on the OpenPOWER platform bought by GENCI and open to the scientific community. We will present on the first results obtained for a set of scientific applications using the available environments (CUDA,OpenACC,OpenMP,â¦), along with results obtained for AI applications using IBM's software distribution PowerAI.

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Keywords:
HPC and Supercomputing, Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8288
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AI & HPC Infrastructure on Oracle Cloud Infrastructure
Marcin Zablocki (Oracle)
Legacy, performance hungry and cutting edge deep learning workloads require best of breed cloud services and hardware. Enterprises require low cost and financial flexibility. Learn how Oracle and NVIDIA have partnered together to solve these cha ...Read More

Legacy, performance hungry and cutting edge deep learning workloads require best of breed cloud services and hardware. Enterprises require low cost and financial flexibility. Learn how Oracle and NVIDIA have partnered together to solve these challenges with a bare-metal NVIDIA Tesla GPU offering to squeeze every ounce of performance at a fraction of the cost. We'll also detail the ability to use NVIDIA GPU CLOUD to streamline the experience for customers to launch and run clusters of GPU Virtual Machines or bare metal instances for AI or HPC workloads. Come see live demos and learn what Oracle Cloud Infrastructure is doing in this space!

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Keywords:
HPC and Supercomputing, Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8528
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CUDA - New Features and Beyond
Stephen Jones (NVIDIA)
CUDA is NVIDIA's parallel computing platform and programming model. You'll learn about new programming model enhancements and performance improvements in the latest release of CUDA, preview upcoming GPU programming technology, gain in ...Read More
CUDA is NVIDIA's parallel computing platform and programming model. You'll learn about new programming model enhancements and performance improvements in the latest release of CUDA, preview upcoming GPU programming technology, gain insight into the philosophy driving the development of CUDA, and see how it will take advantage of current and future GPUs. You'll also learn about NVIDIA's vision for CUDA and the challenges for the future of parallel software development.   Back
 
Keywords:
HPC and Supercomputing, GTC Europe 2018 - ID E8128
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From Remote Graphics Workstation to HPC to Machine Learning - GPU for every workload in Azure - Presented by Microsoft
Tariq Sharif (Microsoft Azure)
Microsoft Azure's N-Series VMs powered by latest NVIDIA GPUs enable a range of new accelerated scenarios. Learn how you can take advantage of GPUs in Azure - from Workstation Graphics and Visualization, to HPC simulation, to training models ...Read More

Microsoft Azure's N-Series VMs powered by latest NVIDIA GPUs enable a range of new accelerated scenarios. Learn how you can take advantage of GPUs in Azure - from Workstation Graphics and Visualization, to HPC simulation, to training models for artificial intelligence. This session will delve deep into today's exciting offerings with live examples and offer a view of what's to come in the future.

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Keywords:
HPC and Supercomputing, GTC Europe 2018 - ID E8500
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Intelligent Video Analytics
Presentation
Media
Decentralized Pavement Distress Detection Based on Deep Learning
Kristina Doycheva (Chair of Computing in Engineering, Ruhr-University Bochum, Germany)
Learn how GPU computing and deep learning can be utilized for the detection of cracks, potholes and patches on road pavement surface. In recent years, the increasing number of vehicles on the road is driving the demand for automated pavement distress ...Read More
Learn how GPU computing and deep learning can be utilized for the detection of cracks, potholes and patches on road pavement surface. In recent years, the increasing number of vehicles on the road is driving the demand for automated pavement distress detection. To respond to this demand, we present a decentralized system for distress detection based on common passenger vehicles. By performing image pre-processing steps and calculating textural features and wavelet transform on GPUs, real-time pavement distress detection is enabled. Deep learning is employed to determine the type of the distress. The approach was tested on 38,000 images and an accuracy of 93% was achieved. To improve the reliability of the pavement distress detection methodology, an ensemble method for distress detection was developed by aggregating results obtained by different vehicles.  Back
 
Keywords:
Intelligent Video Analytics, Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8174
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Deep Learning To Expedite Check Out In Retail
ALBERT CLIMENT (PERVASIVE TECHNOLOGIES)
Learn how to develop an Artificial Intelligence system to localize and recognize food on trays to generate a purchase ticket in a check out process.
(1) Solving a real business problem using Deep Learning advanced technology based on obje ...Read More

Learn how to develop an Artificial Intelligence system to localize and recognize food on trays to generate a purchase ticket in a check out process.
(1) Solving a real business problem using Deep Learning advanced technology based on object detection and localization.
(2) Combining a pipeline of models to improve accuracy, precision and with reasonable recall levels.
(3) Discovering how to develop and train a model in the cloud to be used embedded in an NVIDIA Jetson TX1 device.

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Keywords:
Intelligent Video Analytics, GTC Europe 2018 - ID E8236
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Dancing in the Dark - People and Object Detection in Thermal Videos
Gary Hilgemann (raypack.ai)
Identifying and analyzing objects on images or video is a well-established area of visual computing using artificial intelligence. But what happens, when there is no light ?. Raypack.ai shows, how you could use ai to analyze images and video streams ...Read More
Identifying and analyzing objects on images or video is a well-established area of visual computing using artificial intelligence. But what happens, when there is no light ?. Raypack.ai shows, how you could use ai to analyze images and video streams originated from thermal cameras and other kinds of sensors. Besides detecting objects, this technology is offering a variety of totally new, outstanding use cases.  Back
 
Keywords:
Intelligent Video Analytics, Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8240
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A Fog Computing Infrastructure for Autonomous Driving in Urban Environments
Marko Bertogna (University of Modena)
Detecting road users in real-time is key to enabling safe autonomous driving applications in crowded urban environments. The talk presents a distributed sensor infrastructure being deployed in the city of Modena (Italy) at the heart of the Itali ...Read More

Detecting road users in real-time is key to enabling safe autonomous driving applications in crowded urban environments. The talk presents a distributed sensor infrastructure being deployed in the city of Modena (Italy) at the heart of the Italian 'Motor Valley'. Modena's Automotive Smart Area (MASA) connects hundreds of smart cameras, supporting embedded GPU modules for edge-side real-time detection, with higher performance GPU (fog) nodes at block level and low latency wireless V2X communication. A distributed deep learning paradigm balances precision and response time to give autonomous vehicles the required sensing support in a densely populated urban environment. The infrastructure will exploit a novel software architecture to help programmers and big data practitioners combine data-in-motion and data-at-rest analysis while providing Real-Time guarantees. MASA; funded under the European project CLASS, is an open testbench where interested partners may deploy and test next-generation AD applications in a tightly connected setting.

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Keywords:
Intelligent Video Analytics, GTC Europe 2018 - ID E8254
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PIXEVIA: AI Based, Computer Vision System for Retail, Parking Lots, and Drones
Mindaugas Eglinskas (PIXEVIA)
Modern computing hardware and NVIDIA Jetson TX1 / TX2 performance create new possibilities for smart city applications and retail, parking lot, and drone industries. We'll present on how the PIXEVIA system covers vision processing and AI tas ...Read More

Modern computing hardware and NVIDIA Jetson TX1 / TX2 performance create new possibilities for smart city applications and retail, parking lot, and drone industries. We'll present on how the PIXEVIA system covers vision processing and AI tasks using deep neural networks; learning using computer generated images for number plate recognition; and self-supervised learning for vehicle detection. We will explore methods for orchestrating and combining information from different type of neural networks (from SSDs, Mask-RCNNs to attention based RNNs). Real-world use cases for parking lots (empty parking space detection, number plate recognition) and retail industries (amount of stock on the shelf calculation, people counting with age and gender recognition) will also be presented.

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Keywords:
Intelligent Video Analytics, GTC Europe 2018 - ID E8341
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Park Smart AISee Box: A Scalable Edge Solution for Smart Cities
Marco Moltisanti (Park Smart s.r.l.)
Learn how Edge Computing can help you find the parking spot right next to you! We will present a scalable end-to-end architecture that, leveraging on Nvidia Jetson computational power to detect free parking spaces, is able to drive the user minimizin ...Read More
Learn how Edge Computing can help you find the parking spot right next to you! We will present a scalable end-to-end architecture that, leveraging on Nvidia Jetson computational power to detect free parking spaces, is able to drive the user minimizing the time spent looking for parking. Using our pre-trained models, we are able to perform the detection at the edge of the cloud, reducing the bandwidth utilization up to 95% with respect to a streaming-based solution. Using Computer Vision and Machine Learning algorithms, the configuration needed to setup the system takes only a few minutes with minimal user interaction. Our optimized with dual boot operating system and support to failover, moreover, guarantees security against malicious intrusions and reliability in the upgrade procedures.  Back
 
Keywords:
Intelligent Video Analytics, Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8352
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Self-Aware Spaces: Developing Scene Understanding With Hemispherical 3D Vision and AI
Michel Findeisen (3dvisionlabs GmbH)
Experience how to make spaces aware of the situation of people and objects. Explore new techniques to build real-time systems that can understand scenes with the help of hemispherical point clouds and AI at the edge. The goal of this session is ...Read More

Experience how to make spaces aware of the situation of people and objects. Explore new techniques to build real-time systems that can understand scenes with the help of hemispherical point clouds and AI at the edge. The goal of this session is to learn new ways of developing scene understanding needed for action and interaction in public spaces or smart homes. The capture, recognition and understanding of all external and internal degrees of freedom of persons and objects and of their respective states give the full information of the observed space.
While hemispherical vision provides advantages for wide-area coverage from a single point of observation, it also introduces new challenges due to its distinct projection geometry. At the example of 3-dimensional people detection and posture recognition, we explain different approaches to use deep neural networks to extract information from hemispherical RGB-D data. The talk focuses on providing an overview over methods, which attendees can be apply to custom projects and run on Jetson in real-time.

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Keywords:
Intelligent Video Analytics, GTC Europe 2018 - ID E8355
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Transforming Transportation Infrastructure with GPU Accelerated Machine Learning
Shaun Howell (Vivacity Labs), Yang Lu (Vivacity Labs)
With billions of real-time datapoints and cutting-edge neural networks, Vivacity Labs is providing deep insights into the behaviour of transport networks and transforming urban mobility infrastructure. Over 2500 GPU accelerated camera sensors have be ...Read More
With billions of real-time datapoints and cutting-edge neural networks, Vivacity Labs is providing deep insights into the behaviour of transport networks and transforming urban mobility infrastructure. Over 2500 GPU accelerated camera sensors have been installed city-wide in Milton Keynes UK, able to count and classify vehicle movements in real-time using deep learning. Live predictive models were built based on a proprietary combination of long short-term memory neural networks and evolutionary algorithms. Descriptive modelling has also been used to identify anomalies, correlations, and patterns in the data. Vivacity Labs is now delivering proof of concept systems which continuously and automatically learn and adapt to optimise traffic networks.  Back
 
Keywords:
Intelligent Video Analytics, GTC Europe 2018 - ID E8427
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Deep learning pipeline from annotation to deployment
Ravi Kiran (Smartcow)
SmartCow will demonstrate deep learning pipeline (Annotation, visualization, training) for large data-sets, various internal tools including SmartCow dynamic HPC container deployment software and inference software on on DGX, annotation framework, vi ...Read More
SmartCow will demonstrate deep learning pipeline (Annotation, visualization, training) for large data-sets, various internal tools including SmartCow dynamic HPC container deployment software and inference software on on DGX, annotation framework, visualisation framework, deployment of deep learning models remotely on edge cameras (Jetson TX2 cameras). Take away: Learn how to setup pipeline for annotation of data sets. Understanding how to setup proper deployment for edge cameras.   Back
 
Keywords:
Intelligent Video Analytics, GTC Europe 2018 - ID E8525
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Medical Imaging
Presentation
Media
AI-enabled Neurology
Sebastien Ourselin (King`s College London, School of Biomedical Engineering and Imaging Sciences)
Recent developments in artificial intelligence, advances in GPU computing hardware and the availability of large scale medical imaging datasets allows us to learn how the human brain truly looks like from a biological, physiological, anatomical ...Read More

Recent developments in artificial intelligence, advances in GPU computing hardware and the availability of large scale medical imaging datasets allows us to learn how the human brain truly looks like from a biological, physiological, anatomical and pathological point-of-view. This learning process can be augmented by Electronic Healthcare Record data, cognitive examinations, and diagnostic/radiological report data, thus providing an integrated view of the human interpretation of neurological diseases. This talk will present how AI models can learn from big and unstructured neurological and neuroradiological data and be used as tools for precision medicine, with the aim of translating advanced imaging technologies and biomarkers to clinical practice, streamline the clinical workflow and improve the quality-of-care. It will also explore the technological translational process, requiring full clinical support, deep algorithmic integration into the radiological workflow, and the deployment of a high-throughput hospital-integrated GPU computational platform

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Keywords:
Medical Imaging, GTC Europe 2018 - ID E8101
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Deep Learning Toolkit for Medical Imaging (DLTK)
Martin Rajchl (Imperial College London)
DLTK is an open-source toolkit providing baseline implementations for efficient experimentation with deep learning methods on biomedical images. DLTK builds on top of TensorFlow, and its high modularity and easy-to-use examples allow for a low-t ...Read More

DLTK is an open-source toolkit providing baseline implementations for efficient experimentation with deep learning methods on biomedical images. DLTK builds on top of TensorFlow, and its high modularity and easy-to-use examples allow for a low-threshold access to state-of-the-art implementations for typical medical imaging problems. Automatic downloading and pre-processing of example datasets allow for running and testing example applications, including medical image segmentation, regression, classification, representation learning, super-resolution and training generative models on biomedical images.

A comparison of DLTK's reference implementations of popular network architectures for image segmentation demonstrates new top performance on the publicly available challenge data "Multi-Atlas Labeling Beyond the Cranial Vault". Additionally, DLTK contains a medical model zoo with downloadable pre-trained models for medical image analysis problems, enabling transfer-learning and direct deployment of evaluated deep learning methods.

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Keywords:
Medical Imaging, Artificial Intelligence and Deep Learning, Radiology, GTC Europe 2018 - ID E8198
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Feature Visualisation Techniques for Medical Image Analysis
Maximilian Baust (Konica Minolta Laboratory Europe)
Learn how feature visualization techniques can be used for deep-learning-based medical image analysis. This talk features an introduction to feature visualization techniques and their practical application to the domain of medical image understanding ...Read More
Learn how feature visualization techniques can be used for deep-learning-based medical image analysis. This talk features an introduction to feature visualization techniques and their practical application to the domain of medical image understanding and computer aided diagnosis. Learn about our latest research on obtaining high quality visualizations for recent network architectures and obtain guidelines for using them for your application. After attending this session, you will be able to answer the following questions: What are the implementation caveats of feature visualization techniques? Which conclusions may I draw from the results? Can I possibly integrate these techniques into a product?  Back
 
Keywords:
Medical Imaging, GTC Europe 2018 - ID E8261
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Expanding Precision Medicine with AI-Powered Integrated Decision Support
We believe that medicine will be more precise and affordable. Physicians will integrate relevant patient data and insights at the point of decision for precise diagnostics. Therapy will be tailored to the characteristics of both the patient and ...Read More

We believe that medicine will be more precise and affordable. Physicians will integrate relevant patient data and insights at the point of decision for precise diagnostics. Therapy will be tailored to the characteristics of both the patient and disease ? resulting in the right treatment for the right patient at the right time. AI-powered decision support could help to balance the need for personalization when it matters and standardization to reduce unwarranted variations.

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Keywords:
Medical Imaging, Genomics, GTC Europe 2018 - ID E8290
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VISUHEALTH - Automated Diabetic Retinopathy Screening at ZEISS
Stich Timo (ZEISS)
Learn how the ZEISS VISUHEALTH platform helps prevent blindness due to Diabetic Retinopathy. Instant screening results, continued screening, and early intervention are pivotal but challenging tasks globally due to limited access to retina specialists ...Read More
Learn how the ZEISS VISUHEALTH platform helps prevent blindness due to Diabetic Retinopathy. Instant screening results, continued screening, and early intervention are pivotal but challenging tasks globally due to limited access to retina specialists, especially in rural locations. ViSUHEALTH allows remote and automatic grading of images taken with non-mydriatic Fundus camera(s). Fundus images are uploaded and securely managed in the Cloud. Grading is offered by remote eye doctors or via our CE certified automated screening algorithm. The performance of the automated screening is on par with the manual results, but it also helps scale the screening capabilities to different needs.   Back
 
Keywords:
Medical Imaging, GTC Europe 2018 - ID E8299
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GPU-Driven Deep Learning Paves New Ways for Drug Discovery Through High-Content Imaging
Sepp Hochreiter (Institute of Bioinformatics / LIT AI Lab, Johannes Kepler University Linz, AT), Günter Klambauer (Institute of Bioinformatics / LIT AI Lab, Johannes Kepler University Linz, AT)
Drug discovery is focused around finding relationships between chemical structure and biological effects of small molecules. Since such models depend on already-investigated chemical structures, they can hardly propose completely novel chemical scaff ...Read More
Drug discovery is focused around finding relationships between chemical structure and biological effects of small molecules. Since such models depend on already-investigated chemical structures, they can hardly propose completely novel chemical scaffolds, a problem which has always been a drawback of traditional drug design. Now, researchers from Johannes Kepler University Linz, together with Janssen Pharmaceuticals, have found a novel way to discover drugs with GPU-based Deep Learning: instead of the chemical structure, they use images of cells that were treated with small molecules, and leverage deep neural networks to find relationships with biological effects. Thus, the image-based strategy can propose completely new chemical scaffolds, since there is no dependency on known, well-investigated chemical structures. In ongoing drug discovery projects, this novel GPU-driven strategy has identified many novel chemical scaffolds and thereby increased the discovery rate of drug candidates by 60 and 250-fold.  Back
 
Keywords:
Medical Imaging, Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8311
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Tackling the Challenges of Next Generation Healthcare with GPUs
Fausto Milletari (NVIDIA), Nicola Rieke (NVIDIA)
Modern healthcare strongly relies on digital information for diagnosis, treatment and intervention. But how can we bridge the computational gap created by the ever-increasing amount of available information? How can we deal with challenges such as lo ...Read More
Modern healthcare strongly relies on digital information for diagnosis, treatment and intervention. But how can we bridge the computational gap created by the ever-increasing amount of available information? How can we deal with challenges such as low latency, scaling, remote access, universality? How can we, ultimately, bring the promise of AI to millions of doctors in the field? In this talk we present and demonstrate the concept of CLARA, our architecture for a virtualised computation medical image instrument. CLARA can fit in existing contexts and provide new means to process information both "on-premises" and in the cloud. Through the power of thousands of Volta V100 CUDA cores we show how complex imaging techniques, DL algorithms, and state-of-the-art visualization can co-exist in a virtual, scalable and accessible infrastructure.  Back
 
Keywords:
Medical Imaging, GTC Europe 2018 - ID E8410
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Deep Annotated Learning for Automated Diabetic Retinopathy Detection Utilizing GPU Based Processing
Jonathan Stevenson (Intelligent Retinal Imaging Systems)
Learn about a multi-step automated grading system for Diabetic Retinopathy. First, a smart pattern matching system highlights the potential lesions present in input color fundus images. In a second phase, the annotated images are classified using a C ...Read More
Learn about a multi-step automated grading system for Diabetic Retinopathy. First, a smart pattern matching system highlights the potential lesions present in input color fundus images. In a second phase, the annotated images are classified using a Convolution Neural Network running over Azure Machine Learning and NVIDIA GPU based architecture. The system achieved very high performance for referable DR on clinical datasets with accuracy up to 97.1%. This process has enabled IRIS clients and their patients to receive higher quality care than available today without the enablement of AI in the clinical workflow.  Back
 
Keywords:
Medical Imaging, GTC Europe 2018 - ID E8442
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Radiomics
Klaus Meier-Hein (German Cancer Research Center (DKFZ))
Radiographic image data uniquely represent the spatio-temporal course of disease progression in patients. This talk will present current methods in medical image computing that aim to systematically extract, measure and utilize this information ...Read More

Radiographic image data uniquely represent the spatio-temporal course of disease progression in patients. This talk will present current methods in medical image computing that aim to systematically extract, measure and utilize this information to optimize diagnosis and treatment. The focus will be on suitable machine learning methods, which have become a key technology for successful image processing. Special challenges in the medical context are limitations in terms of data availability, inherent data noise and the lack of high quality annotated training data. The lecture will discuss current ideas and approaches to solving these problems, with relevance potentially not only in medicine but also in other applications.

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Keywords:
Medical Imaging, GTC Europe 2018 - ID E8481
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Professional Visualisation
Presentation
Media
Augmented Reality for the Breeding and Optimization of Food and Medicine
Ryan Hooks (Huxley)
Huxley is utilizing multispectral imaging via AR/AI to assist agronomists in the realm of plant phenotyping. Collaborating with Wageningen University and other top organizations, we are is creating real-time analysis of Controlled Environmental Agric ...Read More
Huxley is utilizing multispectral imaging via AR/AI to assist agronomists in the realm of plant phenotyping. Collaborating with Wageningen University and other top organizations, we are is creating real-time analysis of Controlled Environmental Agriculture. The global plant industry from food, flora, medicine, to the future of CRISPR, is currently is a 4 trillion dollar plus industry. The self-driving car ecosystem has 250+ companies, while plant sciences has very few. 2018 is the year that mobile GPU capabilities can give beginner labor in any language the ability to detect diseases early saving 5-10% of crops, while increasing production by up to 30%. With the same advanced greenhouse systems, China only gets 20% of the yield as a grower from the Netherlands. With AI/AR we aim to help the world grow Dutch. 98% less water, 98% less nutrient input, 2/3 less carbon emissions, while growing 10x per m2 with little to no pesticides. Labor adoption and retention will accelerate with the advancements of deep learning, creating food, medicine, and water security for all.  Back
 
Keywords:
Professional Visualisation, GTC Europe 2018 - ID E8118
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User Experience is Key to VDI Success, Colour Accuracy is Key to User Experience
Nachiket Karmarkar (NVIDIA), Simon Schaber (NVIDIA)
The latest operating systems like Windows 10 or Server 2016 include graphically rich features in its user interface. In addition to this, contemporary applications built to run on top of these modern operating systems further contribute to GPU c ...Read More

The latest operating systems like Windows 10 or Server 2016 include graphically rich features in its user interface. In addition to this, contemporary applications built to run on top of these modern operating systems further contribute to GPU consumption. Therefore it is important to have a GPU for your traditional VDI or any cloud enabled desktop deployment to satisfy the number one user demand, which is the best in class user experience. But,
- How can we measure user experience?
- How can we find out the perfect protocol?
- What is that perfect combination of remote protocol policies?
- What is the perfect codec that best fits to your use case?

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Keywords:
Professional Visualisation, GTC Europe 2018 - ID E8205
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Multi-User Predictive Rendering on Remote Multi-GPU Clusters
Joël Randrianandrasana (University of Reims Champagne-Ardenne)
Many stages of the industry workflow have been benefiting from CAD software applications and real-time computer graphics for decades allowing manufacturers to perform team project reviews and assessments while decreasing the need for expensive physic ...Read More
Many stages of the industry workflow have been benefiting from CAD software applications and real-time computer graphics for decades allowing manufacturers to perform team project reviews and assessments while decreasing the need for expensive physical mockups. However, when it comes to the perceived quality of the final product, more sophisticated physically based engines are often preferred though involving huge computation times. In this context, our work aims at reducing this gap by providing a predictive rendering solution leveraging the computing resources offered by modern multi-GPU supercomputers. To that end, we propose a simple static load balancing approach leveraging the stochastic nature of Monte Carlo rendering. Our solution efficiently exploits the available computing resources and addresses the industry collaboration needs by providing a real-time multi-user web access to the virtual mockup.  Back
 
Keywords:
Professional Visualisation, HPC and Supercomputing, GTC Europe 2018 - ID E8224
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Long Story Short - Don't Feed These Animals
Don't Feed These Animals is Nebula Studios first short animation film. It's a fully independent project that started from one single character by Jose Alves da Silva. A bespoke international team was built and we were lucky enough to hav ...Read More

Don't Feed These Animals is Nebula Studios first short animation film. It's a fully independent project that started from one single character by Jose Alves da Silva. A bespoke international team was built and we were lucky enough to have global supporters joining us in what has become quite a ride. We'll share the full behind the scenes & set up story since DFTA's inception, including how Nvidia was essential to our decision of shifting from CPU to GPU render.

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Keywords:
Professional Visualisation, GTC Europe 2018 - ID E8344
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Simulating Lighting Conditions in Production Ergonomics with NVIDIA OptiX
Andreas Dietrich (ESI Group)
Ergonomics is an important aspect engineering of manufacturing systems andmaintenance procedures of new products for both physical and virtual envronments . A specific case is the prediction of operator or technician visibility under real world ...Read More

Ergonomics is an important aspect engineering of manufacturing systems andmaintenance procedures of new products for both physical and virtual envronments . A specific case is the prediction of operator or technician visibility under real world lighting conditions. For example, when simulating how efficiently a worker will be able to operate a planned system, it is necessary to evaluate early on how this would be affected by a given illumination situation. The ability to digitally design for manufacturability or serviceability, while taking into account human factors, directly influences the potential profitability of new products.  In this session, we will talk about how NVIDIA's OptiX and RTX ray tracing technologies can be leveraged to simulate the propagation of light in environments with complex geometric topology on GPUs. A special focus will be on the OptiX AI denoiser, which masks Monte-Carlo noise that is stemming from the underlying numerical integration methods. We will show how this has been integrated into ESI's Helios visualization framework, before we demonstrate the system through practical examples

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Keywords:
Professional Visualisation, Virtual and Augmented Reality, GTC Europe 2018 - ID E8371
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Sharing Physically Based Materials between Renderers with MDL
Jan Jordan (NVIDIA), Lutz Kettner (NVIDIA)
We'll discuss the basics of NVIDIA's MDL, showing how a single material can be used to define matching appearances between different renderers and rendering techniques. End users will learn how physically based definitions can be defined ...Read More

We'll discuss the basics of NVIDIA's MDL, showing how a single material can be used to define matching appearances between different renderers and rendering techniques. End users will learn how physically based definitions can be defined, while developers will learn what's entailed in supporting MDL within their own products or renderers.

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Keywords:
Professional Visualisation, GTC Europe 2018 - ID E8392
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Collaborative Architectural Design Across Continents at KPF with NVIDIA Holodeck
Cobus Bothma (KPF)
During this session, we will present our development and exploration of multi user collaborative VR, using NVIDIA Holodeck, on large international projects. KPF has 7 global offices working as one large firm and with the increase for high level colla ...Read More
During this session, we will present our development and exploration of multi user collaborative VR, using NVIDIA Holodeck, on large international projects. KPF has 7 global offices working as one large firm and with the increase for high level collaboration, we are continuously looking for ways to improve communication while reducing meeting and travel times. Testing remote collaborative VR environments to ensure our designs are communicated efficiently between teams and our stakeholders are especially valuable during the early fast iterative design stages of a project. This presentation should give you a real world overview of test cases for NVIDIA Holodeck on global projects.  Back
 
Keywords:
Professional Visualisation, Virtual and Augmented Reality, GTC Europe 2018 - ID E8400
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Bringing the Arnold Renderer to the GPU
Roland Reyer (Autodesk)
Arnold is a high quality production renderer for visual effects in film and feature animation used by more than 300 studios worldwide on projects such as Blade Runner 2049 and Game of Thrones. Arnold was instrumental in the shift toward physical ...Read More

Arnold is a high quality production renderer for visual effects in film and feature animation used by more than 300 studios worldwide on projects such as Blade Runner 2049 and Game of Thrones. Arnold was instrumental in the shift toward physically-based light transport simulation in production rendering; in fact, this role was recognized with an Academy Award in 2017. Arnold's success is rooted in its ability to efficiently produce artifact-free images of dynamic scenes with massive complexity while simplifying the user's workflow.
Autodesk will be demonstrating GPU acceleration inside Arnold using NVIDIA OptiX.

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Keywords:
Professional Visualisation, GTC Europe 2018 - ID E8505
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Mesh Shaders in Turing
Patrick Mours (NVIDIA)
We'll give an introduction to mesh shaders, a new programmable geometric shading pipeline first exposed in the Turing architecture. These new shaders bring the compute programming model to the graphics pipeline as threads are used cooperativ ...Read More

We'll give an introduction to mesh shaders, a new programmable geometric shading pipeline first exposed in the Turing architecture. These new shaders bring the compute programming model to the graphics pipeline as threads are used cooperatively to generate compact meshes (meshlets) directly on the chip for consumption by the rasterizer. Applications and games dealing with high-geometric complexity benefit from the flexibility of the two-stage approach, which allows efficient culling, level-of-detail techniques as well as procedural generation.

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Keywords:
Professional Visualisation, GTC Europe 2018 - ID E8515
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Deconstructing the 'Speed of Light' - Porsche, NVIDIA RTX and Unreal Engine 4 (Part 2)
Minjie Wu (EPIC)
The 'Speed of Light' is a fully dynamic ray-traced automotive showcase developed by Epic Games and Nvidia in collaboration with Porsche, running on Unreal Engine 4 and Nvidia's Quadro RTX. This in-depth presentation is split into two ...Read More

The 'Speed of Light' is a fully dynamic ray-traced automotive showcase developed by Epic Games and Nvidia in collaboration with Porsche, running on Unreal Engine 4 and Nvidia's Quadro RTX. This in-depth presentation is split into two separate sessions. Join us for Part 2 as Epic wraps-up their deep-dive by covering shading, rendering and performance optimizations in a real-time ray-traced environment using production examples from the Speed of Light. Make sure you register for the first session E8518!

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Keywords:
Professional Visualisation, GTC Europe 2018 - ID E8519
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Introduction to NVIDIA OptiX
Martin-Karl Lefrancois (NVIDIA)
The presentation is an introduction to NVIDIA OptiX - a sophisticated library for performing GPU ray tracing. You'll get an overview of the NVIDIA OptiX ray-tracing pipeline and learn about its programmable components for high-performance ra ...Read More

The presentation is an introduction to NVIDIA OptiX - a sophisticated library for performing GPU ray tracing. You'll get an overview of the NVIDIA OptiX ray-tracing pipeline and learn about its programmable components for high-performance ray tracing on the GPU. NVIDIA OptiX is used in many domains, from rendering to acoustic modeling to scientific visualization. We'll review its features and present code samples to demonstrate best practices for writing a high-performance ray tracer using its programming model.

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Keywords:
Professional Visualisation, GTC Europe 2018 - ID E8531
Radiology
Presentation
Media
Deep Semantic Lung Segmentation for Tracking Clinical Biomarkers of Chronic Obstructive Pulmonary Disease
Christian Hundt (Johannes Gutenberg University, Mainz), Hinrich B. Winther (Hannover Medical School, Hannover)
Globally, chronic lung diseases are the fourth leading cause of death. Clinical parameters for chronic obstructive pulmonary disease (COPD) are of paramount importance in determining clinical parameters for the identification of biomarkers for t ...Read More

Globally, chronic lung diseases are the fourth leading cause of death. Clinical parameters for chronic obstructive pulmonary disease (COPD) are of paramount importance in determining clinical parameters for the identification of biomarkers for treatment and therapy monitoring. Present a robust Deep Learning pipeline that allows for the prediction of voxel-wise labels of lung lobes in 4D MRI perfusion maps, trained end-to-end without manual interaction. Training can either be accomplished in less than a week on a consumer-scale dual socket workstation with two attached Tesla P40 accelerators or within a day on a DGX-1 Volta. The resulting segmentation maps and derived clinical parameters exhibit high concordance with the ground truth.

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Keywords:
Radiology, Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8276
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Robotics
Presentation
Media
Embedded GPUs for Subsea Robotic 3D Vision and AI
Iain Wallace (Rovco)
Learn how NVIDIA Jetson can be applied to high performance embedded video applications in the harshest of environments. With the advent of ever more powerful embedded GPUs, it's now possible to bring machine intelligence to previously imposs ...Read More
Learn how NVIDIA Jetson can be applied to high performance embedded video applications in the harshest of environments. With the advent of ever more powerful embedded GPUs, it's now possible to bring machine intelligence to previously impossible locations. Rovco are at the forefront of applied machine intelligence underwater, providing subsea survey services based on 3D computer vision and AI data analysis. We show how Jetson is perfect for embedded intelligence applications, with high performance video encoders and powerful GPU for AI applications in a compact, low-power package.  Back
 
Keywords:
Robotics, Autonomous Machines, GTC Europe 2018 - ID E8184
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Object Detection Training: An Online Learning Pipeline for Humanoid Robots
Elisa Maiettini (Istituto Italiano di Tecnologia), Giulia Pasquale (Istituto Italiano di Tecnologia)
This talk will feature the visual system we devised to train, within a few seconds, our R1 humanoid robot to detect multiple novel objects in a given scene. We will present our recently proposed on-line detection pipeline, which combines Faster R-CNN ...Read More
This talk will feature the visual system we devised to train, within a few seconds, our R1 humanoid robot to detect multiple novel objects in a given scene. We will present our recently proposed on-line detection pipeline, which combines Faster R-CNN with one of the fastest kernel based methods, FALKON, to efficiently address the computationally challenging task of training an object detector in few seconds. By relying on a quick bootstrapping approach, the proposed algorithmic solution provides a 60x speedup in training with respect to standard region based methods, and is also in terms of prediction accuracy. Quantitative results will be shown with a demonstration of the system, which can exploit GPU acceleration either from a Geforce GTX 1080 Ti or two Jetson TX2 cards on board R1.  Back
 
Keywords:
Robotics, Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8346
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Smarter Humanoid Companion - Our Latest Developments on SoftBank's Pepper Robot with an Embedded Jetson TX2
Alexandre Mazel (SoftBank Robotics)
Learn how our world can be understood better and faster by our robotic companions thanks to embedded GPUs. In this talk, we will present developments done since last year thanks to the Jetson TX2 embedded in SoftBank's Pepper, the world' ...Read More

Learn how our world can be understood better and faster by our robotic companions thanks to embedded GPUs. In this talk, we will present developments done since last year thanks to the Jetson TX2 embedded in SoftBank's Pepper, the world's leading affordable humanoid robot. This work revolves around human gesture recognition and better human robot interaction. A live demo of the autonomous Pepper Robot embedding the Jetson TX2 and interacting on stage will be done during the session.

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Keywords:
Robotics, GTC Europe 2018 - ID E8426
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Metric Learning to Reduce Deep Learning's Resource Hunger
The Duy Nguyen (GESTALT Robotics GmbH)
This talk shows how Deep Metric Learning is used to reduce the data hunger of Deep Learning models for object recognition and gives them the ability to learn on-the-fly. Deep Learning for automated object recognition has shown to be highly effec ...Read More

This talk shows how Deep Metric Learning is used to reduce the data hunger of Deep Learning models for object recognition and gives them the ability to learn on-the-fly. Deep Learning for automated object recognition has shown to be highly effective and useful for various applications. However, practitioners need a large amount of labelled data to train robust models. On top, the time ocnsuming training process has to be repeated every time an object class is added to the portfolio. This talk proposes applying Deep Metric learning to overcome these two problems. Instead of learning to recognize a particular set of objects. We train the model to learn similarities between them. This fine task modification results in models which are able to compare known objects with unknown ones. Adding new objects to the portfolio only requires adding a few addiotonal images to the database. No retraining is required. As a use case, we demonstrate an automated stock monitoring system which recognises the products going in and out of a store. The data collected can be used for various applications including stocktaking, computing statistics and worker guidance.

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Keywords:
Robotics, Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8455
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How Robots Can Learn to Master Dynamic, Complex Tasks through Human Interaction
Ronnie Vuine (micropsi industries)
This talk is about driving industrial robots from Jetson TX2: The difficulties of getting pixels from two industrial cameras into the system and a control signal out at high frequencies and under real-time conditions. micropsi industries MIRAI is a m ...Read More
This talk is about driving industrial robots from Jetson TX2: The difficulties of getting pixels from two industrial cameras into the system and a control signal out at high frequencies and under real-time conditions. micropsi industries MIRAI is a machine learning-driven real-time control system for industrial robots developed on x86, and the talk will relate the experiences made when getting this to run on Tegra: numbafying CPU-intensive algorithms, learning the quirks of Tegra CPU management, going from TensorFlow to a hand-rolled TensorRT integration and back â and doing all this in Python.  Back
 
Keywords:
Robotics, Artificial Intelligence and Deep Learning, GTC Europe 2018 - ID E8461
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Number Understanding Modelling in a Behavioural Embodied Robotic System (NUMBERS)
Alessandro Di Nuovo (Sheffield Hallam University)
The talk presents the current developments of the NUMBERS project highly interdisciplinary research program in Cognitive Developmental Robotics to construct a novel artificial cognitive model of mathematical cognition that imitates human-like le ...Read More

The talk presents the current developments of the NUMBERS project highly interdisciplinary research program in Cognitive Developmental Robotics to construct a novel artificial cognitive model of mathematical cognition that imitates human-like learning approaches for developing number understanding.
The project aims to provide a proof-of-concept and the scientific and technological bases for novel robots capable of abstract and symbolic processing, which is required for improving their cognitive performance and their social interaction with human beings.
During the talk, the current experimental results will be reviewed to give evidence of improved performance thanks to the embodiment.

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Keywords:
Robotics, GTC Europe 2018 - ID E8502
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Virtual and Augmented Reality
Presentation
Media
Dynamic Light Sculpting: Creating True 3D Holograms with GPUs
Darran Milne (VividQ), Tom Durrant (VividQ)
True holography, or "dynamically sculpted light", allows for the reproduction of a full 3D light field in a display, complete with colour and depth. Hence, it is perhaps the ultimate goal for the display and VR/AR industries. With the ...Read More

True holography, or "dynamically sculpted light", allows for the reproduction of a full 3D light field in a display, complete with colour and depth. Hence, it is perhaps the ultimate goal for the display and VR/AR industries. With the advent of powerful GPU computing, it is now for the first time becoming possible to compute holograms - in this full 3D sense- in real time. This is what we are working on at VividQ.

Audience members will be given a brief introduction to how 3D holograms work, using diffractive optics, and why they are so expensive to compute. We will cover the standard approach to computation, and our progress in speeding up the computation using CUDA, taking the calculation time of a holographic frame from many minutes down to milliseconds. Since a full light field is created, instead of using stereographic techniques, the visual conflicts which contribute to headaches in many VR and AR devices are avoided. There will also be the opportunity to see videos of AR holograms, demonstrating how the images focus and defocus at different focal depths, and exhibit expected optical effects such as parallax.

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Keywords:
Virtual and Augmented Reality, HPC and Supercomputing, GTC Europe 2018 - ID E8209
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NVIDI's VR Insights: OpenGL, Vulkan and Dual-Input HMDs
Ingo Esser (NVIDIA), Robert Menzel (NVIDIA)
This talk will feature an update on what's happening in the professional VR space at NVIDIA. We first introduce OpenGL and Vulkan VR functionality, and then will talk about how to drive dual-input HMDs from two GPUs efficiently. ...Read More

This talk will feature an update on what's happening in the professional VR space at NVIDIA. We first introduce OpenGL and Vulkan VR functionality, and then will talk about how to drive dual-input HMDs from two GPUs efficiently.

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Keywords:
Virtual and Augmented Reality, GTC Europe 2018 - ID E8300
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NVIDIA Holodeck
David Weinstein (NVIDIA), Hilda Espinal (Cannondesign)
Holodeck is NVIDIA's advanced technology platform for Virtual Reality. We will begin this session by reviewing the motivation and goals of Holodeck. We will then highlight the new features from our most recent Holodeck release. The latest ve ...Read More

Holodeck is NVIDIA's advanced technology platform for Virtual Reality. We will begin this session by reviewing the motivation and goals of Holodeck. We will then highlight the new features from our most recent Holodeck release. The latest version adds support for architectural design review, including model review at scale, teleporting to different floors, and specifying points of interest. As a feature of this session, Hilda Espinal, CTO of CannonDesign, will join us to share how her firm is using Holodeck in customer projects, how customers are reacting to this new technology, and her perspective on how VR will impact architectural design in coming years. CannonDesign is a leading global design firm that was one of the earliest adopters of Holodeck. Come hear this talk to learn all about the technology, and then visit the VR Village to experience the new Holodeck features firsthand!

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Keywords:
Virtual and Augmented Reality, GTC Europe 2018 - ID E8433
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Next Generation VR with Large FoV and High Resolution with StarVR and NVIDIA VRWorks
Marc Piuzzi (STARVR CORP.)
We will talk about the implementation of new features in VR and illustrate examples of how StarVR combined with NVIDIA technology is finally providing a natural life like immersion revolutionizing VR applications for industries as various as design, ...Read More
We will talk about the implementation of new features in VR and illustrate examples of how StarVR combined with NVIDIA technology is finally providing a natural life like immersion revolutionizing VR applications for industries as various as design, manufacturing, training or film and gaming. We will also cover early integrations in UE4,VRED,Techviz. The main drawbacks of current generation VR headsets are the narrow field of view (FoV) and the low perceived resolution resulting on a visible pixel grid which, combined, alter the immersive feeling for the user. StarVR is developing a new VR headset combining a large FoV of 210° on the Horizontal axis and 130° on the Vertical axis and two high resolution OLED panels with a combined resolution of 5K, aiming for an improved VR experience. However, rendering high quality VR content with a high and constant framerate to provide a smooth experience is a great technological challenge for graphics cards. To tackle that problem, StarVR has combined VRWorks technologies such as Quadro VR SLI for rendering one eye per GPU and MRS/LMS with the embedded Tobii Eyetracker resulting in a huge boost of performance with Pascal and Volta based GPUs  Back
 
Keywords:
Virtual and Augmented Reality, Professional Visualisation, GTC Europe 2018 - ID E8437
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Converging VR, AR, 3D Printing and AI: Art as the Vehicle for Driving Technology in Africa
Rick Treweek (The Digital Foundry), Gareth Steele (The Digital Foundry)
This talk examines the convergence of different technologies like AR, VR, AI, 3D printing and more to solve problems in the arts space and lower the entry of barrier for aspiring artists. Rick Treweek, Director of Technology, and Gareth Steele, ...Read More

This talk examines the convergence of different technologies like AR, VR, AI, 3D printing and more to solve problems in the arts space and lower the entry of barrier for aspiring artists. Rick Treweek, Director of Technology, and Gareth Steele, Art Director at The Digital Foundry, will share their knowledge of how these technologies can be used to promote technology across varied audiences, particularly in the African ecosystem. The merging of technology is opening up a new toolset to utilise and expand art practices and allows creation without extensive technical knowledge or experience.

This knowledge is not only applicable in art, but is valuable for traditional and emerging tech companies as well: Custom hardware creation thanks to 3D printing allows us to experiment with alternative delivery mechanisms for Virtual and Augmented Reality, and to rapidly prototype new tools or components. Coupled with the powerful ability to design and visualize within VR for 3D print, we are exploring new ways of bridging the gap between digital & physical and also create digital twins by using technologies like 3D scans and photogrammetry, that are all profiting from GPU acceleration.

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Keywords:
Virtual and Augmented Reality, GTC Europe 2018 - ID E8460
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Multi-Sensual Experiences Based on VR Technology at Audi DesignCheck
Daniel Hauser (Audi AG)
The presentation gives a deep insight into the virtual development stages at Audi design check. It shows how we react to new customer wishes and how we virtually design, conceptualize and develop the interior of the future. In the past we have focuse ...Read More
The presentation gives a deep insight into the virtual development stages at Audi design check. It shows how we react to new customer wishes and how we virtually design, conceptualize and develop the interior of the future. In the past we have focused on 2d power walls. Today we have the possibility to move freely in interactive rooms and to make the car experienceable. To drive on virtual roads or to communicate in collaborative spaces by using 3d data. Starting from the concept phase to the start of production. An impressive leap forward. Vorsprung durch Technik.  Back
 
Keywords:
Virtual and Augmented Reality, Professional Visualisation, GTC Europe 2018 - ID E8465
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Investing in XR. Where's the smart money going?
Dave Haynes (HTC)
Vive X is HTC's global program to build the XR ecosystem by investing in startups. With over 80 portfolio companies and local hubs in the US and Asia, the program is now active in Europe, where over 150 startups have been looked at in the la ...Read More

Vive X is HTC's global program to build the XR ecosystem by investing in startups. With over 80 portfolio companies and local hubs in the US and Asia, the program is now active in Europe, where over 150 startups have been looked at in the last six months. This talk will share the insights gained from this activity as well as discussing the latest investment trends in the sector generally. Who is investing in AR and VR and what types of ventures are most successful in getting funded? Where do the biggest opportunities lie and what are some key challenges that still need to be addressed? This talk is for you whether you're a startup founder, investor or just interested in the latest innovations happening in XR.

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Keywords:
Virtual and Augmented Reality, GTC Europe 2018 - ID E8517
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Fast Encoding Techniques for Mobile Virtual Reality
Jorge Ruano Puente (Nokia), Juan Casal Martin (Nokia)
The session will explain how ultra-low latency techniques for video encoding and transmission can be applied for creating advanced XR experiences anywhere in the world, just using a mobile phone connected to a 5G network. The main challenge for ...Read More

The session will explain how ultra-low latency techniques for video encoding and transmission can be applied for creating advanced XR experiences anywhere in the world, just using a mobile phone connected to a 5G network. The main challenge for creating a proper XR experience through telecommunications networks is to achieve a total latency (" motion to photon") low enough for avoiding desynchronizations between the brain expectations and the signals that the eye is receiving. The use of NVIDIA NVENC plus other protocols like HTTP Chunked Transfer Encoding make possible to achieve a very low latency over a universal protocol like HTTP that is easily transmitted across mobile networks, making possible XR experiences without a physical connection between render engine and the terminal.

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Keywords:
Virtual and Augmented Reality, GTC Europe 2018 - ID E8521
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