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GTC ON-DEMAND

5G & Edge
Presentation
Media
Abstract:
We'll talk about applying ML/AI to the crucial task of identifying and isolating faults in computer and telecommunications networks. A problem with part or all of a single device can quickly propagate through the network, making it essential to iden ...Read More
Abstract:
We'll talk about applying ML/AI to the crucial task of identifying and isolating faults in computer and telecommunications networks. A problem with part or all of a single device can quickly propagate through the network, making it essential to identify a fault before it causes a hardware component to fail. We'll discuss cost-effective expert systems for network monitoring that are designed to minimize the number of service-affecting incidents, while keeping development, personnel, and maintenance costs at an acceptable level. We'll also explain how streaming telemetry enables access to real-time, model-driven, and analytics-ready data that can help with network automation, traffic optimization, and preventive troubleshooting.  Back
 
Topics:
5G & Edge, Data Center & Cloud Infrastructure
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9758
Streaming:
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AI & Deep Learning Research
Presentation
Media
Abstract:
Well host a dialogue between Ciscos Kapil Bakshi and NT Concepts Eric Miles to discuss the future of weapon system maintenance. Kapil is a distinguished solutions engineer supporting Ciscos federal cloud and AI and machine learning practice, and Eric ...Read More
Abstract:
Well host a dialogue between Ciscos Kapil Bakshi and NT Concepts Eric Miles to discuss the future of weapon system maintenance. Kapil is a distinguished solutions engineer supporting Ciscos federal cloud and AI and machine learning practice, and Eric is the director of operations at NT Concepts. Theyll outline how the Department of Defense is challenged by mission readiness. The two will identify the real-world relationships between data, applications, infrastructure, cybersecurity, and operational resiliency. After our panel, attendees can attend our booth to engage with Cisco and NT Concepts experts to explore the potential of mission AI and machine learning.  Back
 
Topics:
AI & Deep Learning Research, AI Application, Deployment & Inference
Type:
Sponsored Talk
Event:
GTC Washington D.C.
Year:
2019
Session ID:
DC91494
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AI Application, Deployment & Inference
Presentation
Media
Abstract:
This talk will provide an overview of what is happening in the world of artificial intelligence as it relates to networking, IT infrastructure, and IoT technologies. We will broadly cover AI topics ranging from machine learning and deep learning to s ...Read More
Abstract:
This talk will provide an overview of what is happening in the world of artificial intelligence as it relates to networking, IT infrastructure, and IoT technologies. We will broadly cover AI topics ranging from machine learning and deep learning to symbolic AI. Applied AI as well as general AI and their hybrids are all critical in solving many of today's complex long tail problems in real-time. Just as the capabilities, business opportunities, and positive benefits of AI are growing at a seemingly exponential rate so are the security vulnerabilities, failure modes, and potential adverse business impacts. We will discuss new hybrid neural symbolic approaches that promise to address these issues while simultaneously opening the door to powerful systems that dynamically learn and reason at multiple levels of abstraction, from raw data to high-level symbolic reasoning. We will cover use cases and solutions ranging from smart city, transportation, manufacturing, to security and networking.  Back
 
Topics:
AI Application, Deployment & Inference, Advanced AI Learning Techniques
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8971
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Abstract:
Craig Morioka, UCLA Adjunct Associate Professor of Radiological Sciences, and Dima Lituiev, Postdoctoral Scholar at the University of California San Francisco, Institute for Computational Health Sciences, will discuss how they empower their fellow fa ...Read More
Abstract:
Craig Morioka, UCLA Adjunct Associate Professor of Radiological Sciences, and Dima Lituiev, Postdoctoral Scholar at the University of California San Francisco, Institute for Computational Health Sciences, will discuss how they empower their fellow faculty, staff, and students with the latest techniques in training and deploying deep neural networks through NVIDIAs Deep Learning Institute (DLI) University Ambassador Program - a new AI and Deep Learning education enablement program for universities. This will include a dive into the benefits of an online learning platform, which uses GPUs in the cloud, by stepping through the DLIs online Image Segmentation and Radiomics labs. The Image Segmentation lab leverages an example from medical image analysis where it is often important to separate pixels corresponding to different types of tissue or cells for the purposes of diagnostics and treatment planning. Dima uses image segmentation in his research to facilitate diagnostics of kidney rejection by analyzing histological slides from patients with kidney transplants. We will explore how the Tensorflow code is structured and how the Tensorboard tool can be used to visualize structure and training dynamics of segmentation models. The focus of the Radiomics lab is detection of the 1p19q co-deletion biomarker using deep learning - specifically convolutional neural networks using the Keras and TensorFlow computing frameworks. Attendees will also learn how they can apply to become a DLI University Ambassador and bring the latest in Deep Learning and AI education to their academic communities.    Back
 
Topics:
AI Application, Deployment & Inference, Deep Learning & AI Frameworks, AI & Deep Learning Business Track (High Level)
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8823
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AI in Healthcare
Presentation
Media
Abstract:
We will talk about how we're using AI to solve problems in healthcare, and specifically in cardiovascular imaging. We built foundational tools for view classification in echocardiography, using NVIDIA GPUs to provide classification- and segmentation ...Read More
Abstract:
We will talk about how we're using AI to solve problems in healthcare, and specifically in cardiovascular imaging. We built foundational tools for view classification in echocardiography, using NVIDIA GPUs to provide classification- and segmentation-based diagnosis of cardiovascular disease. We'll show how we apply this work toward certain unmet needs in cardiology, using methods that are highly applicable across several fields in medicine.  Back
 
Topics:
AI in Healthcare, Medical Imaging & Radiology
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9104
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Accelerated Data Science
Presentation
Media
Abstract:
Well discuss how, despite attention and sizable investments, only a small set of companies have successfully brought machine learning and AI from experimental stages to production at scale. Its critical to operationalize machine learning efficiently ...Read More
Abstract:
Well discuss how, despite attention and sizable investments, only a small set of companies have successfully brought machine learning and AI from experimental stages to production at scale. Its critical to operationalize machine learning efficiently and effectively. By supporting many customers in deploying machine learning in their production environments, we have learned about the significant challenges enterprises face. Well provide recommendations on how to address these obstacles.  Back
 
Topics:
Accelerated Data Science, AI Application, Deployment & Inference
Type:
Sponsored Talk
Event:
GTC Washington D.C.
Year:
2019
Session ID:
DC91463
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Artificial Intelligence and Deep Learning
Presentation
Media
Abstract:
Data is the lifeblood of an enterprise, and it's being generated everywhere. To overcome the challenges of data gravity, data analytics, including machine learning, is best done where the data is located. Come to this session to understand h ...Read More
Abstract:

Data is the lifeblood of an enterprise, and it's being generated everywhere. To overcome the challenges of data gravity, data analytics, including machine learning, is best done where the data is located. Come to this session to understand how to overcome the challenges of machine learning everywhere.

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Topics:
Artificial Intelligence and Deep Learning
Type:
Special Event
Event:
GTC Israel
Year:
2018
Session ID:
SIL8155
Streaming:
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Abstract:
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 learn ...Read More
Abstract:

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.

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Topics:
Artificial Intelligence and Deep Learning, AI & Deep Learning Business Track (High Level)
Type:
Talk
Event:
GTC Europe
Year:
2018
Session ID:
E8356
Streaming:
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Abstract:
Machine learning and deep learning applications are revolutionizing how we as consumers interact with our compute devices by imbuing them with speech recognition, machine vision, and other perceptual capabilities. We are now seeing new advanceme ...Read More
Abstract:

Machine learning and deep learning applications are revolutionizing how we as consumers interact with our compute devices by imbuing them with speech recognition, machine vision, and other perceptual capabilities. We are now seeing new advancements in AI which move from simple pattern recognition and perceptual processing to much deeper semantic processing. These new advancements in essence bridge the gap between machine learning techniques, including deep learning, and symbolic artificial intelligence. We'll cover the new capabilities and use cases Cisco is targeting with this new breakthrough technology. In addition, we'll discuss the core enabling technical building blocks and projects such as InfoGAN's and Ben Goertzel's OpenCog project.

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Topics:
Artificial Intelligence and Deep Learning
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7828
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Abstract:
Artificial intelligence and machine learning are gaining adoption beyond the lab into real business initiatives. It is critical to have an architectural approach ensuring that AI/ML deployments can scale from proof-of-concept to production with data ...Read More
Abstract:
Artificial intelligence and machine learning are gaining adoption beyond the lab into real business initiatives. It is critical to have an architectural approach ensuring that AI/ML deployments can scale from proof-of-concept to production with data pipeline extending from data sources in IoT sensors, remote offices, and data center. In this session we will discuss how Cisco infrastructure can support data pipelines from the end of the earth, to the data center, and even to the cloud. You will find out how infrastructure performance, scale and flexibility can help you to accelerate and operationalize your data pipeline for successful enterprise-grade AI/ML projects.  Back
 
Topics:
Artificial Intelligence and Deep Learning
Type:
Talk
Event:
MWC
Year:
2019
Session ID:
mwcla925
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Autonomous Vehicles
Presentation
Media
Abstract:
We present our experience of running computationally intensive camera-based perception algorithms on NVIDIA GPUs. Geometric (depth) and semantic (classification) information is fused in the form of semantic stixels, which provide a rich and comp ...Read More
Abstract:

We present our experience of running computationally intensive camera-based perception algorithms on NVIDIA GPUs. Geometric (depth) and semantic (classification) information is fused in the form of semantic stixels, which provide a rich and compact representation of the traffic scene. We present some strategies to reduce the computational complexity of the algorithms. Using synthetic data generated by the SYNTHIA tool, including slanted roads from a simulation of San Francisco city, we evaluate performance latencies and frame rates on a DrivePX2-based platform.

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Topics:
Autonomous Vehicles, Computer Vision, HPC and AI
Type:
Talk
Event:
GTC Europe
Year:
2017
Session ID:
23196
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Computer Vision
Presentation
Media
Abstract:
We present an approach of using real time path tracing in combination with traditional deferred techniques. This method allows to use most elements of a traditional rendering pipeline (like direct light and post effects) and keep the BVH ray tra ...Read More
Abstract:

We present an approach of using real time path tracing in combination with traditional deferred techniques. This method allows to use most elements of a traditional rendering pipeline (like direct light and post effects) and keep the BVH ray traversal usage at a minimum. In combination with adaptive filtering, GPU data streaming and mesh preprocessing, this technique allows for real time frame rates up to Virtual Reality usage on a single GPU. The robust implementation is used for architectural visualization but can also be used at games and other areas with a wide range of direct and indirect lighting phenomena. We finally compare our results with our offline path tracer implementation.

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Topics:
Computer Vision, Intelligent Machines, IoT & Robotics
Type:
Talk
Event:
GTC Europe
Year:
2017
Session ID:
23026
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Abstract:
In this poster we compare the performance of a detection network when running in different devices. We deploy a YOLOv2 net in TK1 and TX1 embedded devices and study their performance in running time. In addition, we also test this network in a ...Read More
Abstract:
In this poster we compare the performance of a detection network when running in different devices. We deploy a YOLOv2 net in TK1 and TX1 embedded devices and study their performance in running time. In addition, we also test this network in a workstation equipped with a TITAN X GPU as an upper bound.
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Topics:
Computer Vision, Intelligent Machines, IoT & Robotics
Type:
Poster
Event:
GTC Europe
Year:
2017
Session ID:
P23026
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Data Center & Cloud Infrastructure
Presentation
Media
Abstract:
Are you doing data science at scale? Do you need a cluster of GPUs to help accelerate machine learning training and inferencing? Does your data pipeline extend beyond the walls of the data center to remote office, retail stores, or IoT sensors? We'l ...Read More
Abstract:
Are you doing data science at scale? Do you need a cluster of GPUs to help accelerate machine learning training and inferencing? Does your data pipeline extend beyond the walls of the data center to remote office, retail stores, or IoT sensors? We'll discuss how Cisco infrastructure can support data pipelines that extend from ends of the earth, to the data center, and even to the cloud with technologies such as NGC on Red Hat OpenShift, NGC on Hortonworks, and Kubeflow. Learn how infrastructure performance, scale, and flexibility can help accelerate, scale, and operationalize your data pipeline.  Back
 
Topics:
Data Center & Cloud Infrastructure, AI & Deep Learning Business Track (High Level)
Type:
Sponsored Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S91019
Streaming:
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Abstract:
Learn how to use containers for efficient GPU utilization to achieve bare-metal performance for computationally intensive workloads. We'll show how NVIDIA tools and libraries can be used to achieve drop-in GPU support and efficient GPU feature integ ...Read More
Abstract:
Learn how to use containers for efficient GPU utilization to achieve bare-metal performance for computationally intensive workloads. We'll show how NVIDIA tools and libraries can be used to achieve drop-in GPU support and efficient GPU feature integration for container runtimes, and illustrate how to leverage system containers to run complex statistical models on NVIDIA GPUs.  Back
 
Topics:
Data Center & Cloud Infrastructure, GPU Virtualization
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8338
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Deep Learning & AI Frameworks
Presentation
Media
Abstract:
Adoption of machine learning (ML) and deep learning has grown at an unprecedented rate in the last few years. With many applications requiring edge compute as well as a strong demand for hybrid and multi cloud no lock-in solutions, customers dem ...Read More
Abstract:

Adoption of machine learning (ML) and deep learning has grown at an unprecedented rate in the last few years. With many applications requiring edge compute as well as a strong demand for hybrid and multi cloud no lock-in solutions, customers demand more flexibility in how models are trained and served. This situation warrants a hybrid cloud approach, enabling ML wherever the data lives with the flexibility to access the cloud when local compute resources are lacking. Google Cloud has collaborated with partners, including NVIDIA and Cisco, to enable a standard open source AI platform, Kubeflow, that's built on Kubernetes to provide a consistent machine learning experience for both on-premise and in the cloud. This platform supports deep integration into NVIDIA stack, including TensorRT and RAPIDS. 

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Topics:
Deep Learning & AI Frameworks, AI Application, Deployment & Inference
Type:
Sponsored Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S91030
Streaming:
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GPU Virtualization
Presentation
Media
Abstract:
The industry-standard graphics performance benchmark tool, SPECviewperf 13, provides valuable insight on GRID profile and Tesla graphic card selection for virtualizing high-performance graphics applications. Learn how Cisco technical marketing engine ...Read More
Abstract:
The industry-standard graphics performance benchmark tool, SPECviewperf 13, provides valuable insight on GRID profile and Tesla graphic card selection for virtualizing high-performance graphics applications. Learn how Cisco technical marketing engineers evaluate performance of converged and hyperconverged platforms with the full spectrum of NVIDIA Tesla GPUs on eight key applications on the two leading desktop broker vendors. We will share our methodology for scoring grid profile/Tesla GPU/server hardware platform combinations for each application in the performance tool. We'll also present our sizing recommendations for these widely used products based on the application user type.  Back
 
Topics:
GPU Virtualization
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9881
Streaming:
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Abstract:
Cisco and NVIDIA partnered with ESRI to create starting point sizing guidance for ArcGIS Pro in the optimal Cisco UCS server with the best fit NVIDIA GPU to deliver three key capabilities of the software: 3D rendering, spatial analytics and deep ...Read More
Abstract:

Cisco and NVIDIA partnered with ESRI to create starting point sizing guidance for ArcGIS Pro in the optimal Cisco UCS server with the best fit NVIDIA GPU to deliver three key capabilities of the software: 3D rendering, spatial analytics and deep learning inferencing – all on the same server

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Topics:
GPU Virtualization
Type:
Talk
Event:
VMWorld
Year:
2019
Session ID:
VM9041
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Abstract:
Modernizing VDI to support the use of common productivity and collaboration applications, video content, graphics intensive Windows 10, and the rising trend of multiple and higher resolution monitors are all driving the demand for more graphics ...Read More
Abstract:

Modernizing VDI to support the use of common productivity and collaboration applications, video content, graphics intensive Windows 10, and the rising trend of multiple and higher resolution monitors are all driving the demand for more graphics computing resources. In this session, learn how customers using Cisco-NVIDIA solutions have turned to GPU virtualization to achieve a native-PC experience in the age of multimedia.

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Topics:
GPU Virtualization
Type:
Talk
Event:
VMWorld
Year:
2019
Session ID:
VM9052
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Medical Imaging & Radiology
Presentation
Media
Abstract:
We will outline strategies designed to incorporate emerging artificial intelligence and machine learning into the clinical practice of diagnostic radiology, the primary entry point for imaging in the U.S. healthcare system. We'll discuss the underly ...Read More
Abstract:
We will outline strategies designed to incorporate emerging artificial intelligence and machine learning into the clinical practice of diagnostic radiology, the primary entry point for imaging in the U.S. healthcare system. We'll discuss the underlying radiology value chain to explain the architecture of existing radiology information management systems for imaging. We will highlight the centrality of imaging in guiding patient care to outline the opportunities and barriers to adopting AI and ML in clinical practice, and we'll explore how AI and ML are poised to transform imaging delivery for certain medical domains to the benefit of patients.  Back
 
Topics:
Medical Imaging & Radiology
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9876
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Other
Presentation
Media
Abstract:
You are invited to learn how Cisco AppDynamics can create a culture of ongoing improvement and openness by making it simple for teams to get the data they want for their role in the DevOps toolchain.
 
Topics:
Other
Type:
Talk
Event:
GTC Israel
Year:
2017
Session ID:
SIL7156
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Abstract:
Machine learning and deep learning applications are revolutionizing how we as consumers interact with our compute devices by imbuing them with speech recognition, machine vision, and other perceptual capabilities. We are now seeing new advanceme ...Read More
Abstract:

Machine learning and deep learning applications are revolutionizing how we as consumers interact with our compute devices by imbuing them with speech recognition, machine vision, and other perceptual capabilities. We are now seeing new advancements in AI which move from simple pattern recognition and sensory data processing to much deeper semantic processing. These new advancements in essence bridge the gap between machine learning techniques, including commoditized deep learning on SIMD GPUs , and the next generation of specialized distributed-memory MIMD hardware for large-scale graph analysis for symbolic artificial intelligence. In this session we will cover the new capabilities and use cases Cisco is targeting with this new breakthrough technology.

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Topics:
Other
Type:
Talk
Event:
GTC Europe
Year:
2017
Session ID:
23346
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Pathology
Presentation
Media
Abstract:
Learn how to prepare pathology whole-slide imaging for a machine learning experiment using open-source tools.
 
Topics:
Pathology, Tools & Libraries
Type:
Tutorial
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9822
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