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GTC ON-DEMAND

Presentation
Media
Abstract:
We'll dive deep into how we use heterogeneous clusters with GPUs for accelerating urban-scale crowd data analysis, simulation, and visualization. Our main contributions are the development of new behavior models that conform to real data, the ability to scale the system by adding computing resources as needed without making programming modifications and the combination of analysis, simulation, and visualization techniques that help us achieve large-scale crowd simulations with realistic behavior.
We'll dive deep into how we use heterogeneous clusters with GPUs for accelerating urban-scale crowd data analysis, simulation, and visualization. Our main contributions are the development of new behavior models that conform to real data, the ability to scale the system by adding computing resources as needed without making programming modifications and the combination of analysis, simulation, and visualization techniques that help us achieve large-scale crowd simulations with realistic behavior.  Back
 
Topics:
In-Situ & Scientific Visualization, Artificial Intelligence and Deep Learning, Computational Physics, HPC and Supercomputing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7272
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Speakers:
,,
Abstract:

Industry trends in the coming years in the race to exascale imply the availability of cluster computing with hundreds to thousands of cores per chip. Programming presents a challenge due to the heterogeneous architecture. Using novel programming models that facilitate this process is necessary. In this talk we present the case of simulation and visualization of crowds. We analyze and compare the use of two programming models: OmpSs and CUDA and show that OmpSs allows us to exploit all the resources combining the use of CPU and GPU taking care of memory management, scheduling, communications and synchronization automatically. We will present experimental results obtained in the Barcelona Supercomputing Center GPU Cluster as well as describe several modes used for visualizing the results.

Industry trends in the coming years in the race to exascale imply the availability of cluster computing with hundreds to thousands of cores per chip. Programming presents a challenge due to the heterogeneous architecture. Using novel programming models that facilitate this process is necessary. In this talk we present the case of simulation and visualization of crowds. We analyze and compare the use of two programming models: OmpSs and CUDA and show that OmpSs allows us to exploit all the resources combining the use of CPU and GPU taking care of memory management, scheduling, communications and synchronization automatically. We will present experimental results obtained in the Barcelona Supercomputing Center GPU Cluster as well as describe several modes used for visualizing the results.

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Topics:
Visualization - In-Situ & Scientific, Data Center & Cloud Infrastructure, Real-Time Graphics, HPC and Supercomputing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2015
Session ID:
S5381
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Abstract:

We discuss several steps in the process for simulating and visualizing large and varied crowds, in real time, for consumer-level computers and graphic cards (GPUs). We discuss methods for simulating, generating, animating and rendering crowds of varied aspect and a diversity of behaviors.

We discuss several steps in the process for simulating and visualizing large and varied crowds, in real time, for consumer-level computers and graphic cards (GPUs). We discuss methods for simulating, generating, animating and rendering crowds of varied aspect and a diversity of behaviors.

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Topics:
Media & Entertainment Summit, Combined Simulation & Real-Time Visualization, Rendering & Ray Tracing, Visual Effects & Simulation
Type:
Talk
Event:
GTC Silicon Valley
Year:
2014
Session ID:
S4229
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Abstract:

We will discuss several steps in the process for simulating and visualizing large and varied crowds, in real time, for consumer-level computers and graphic cards (GPUs). Animating varied crowds using a diversity of models and animations (assets) is complex and costly. One needs models that are expensive if bought, take a long time to model, and consume too much memory and computing resources. We have developed methods for generating, simulating and animating crowds of varied aspect and a diversity of behaviors. Efficient simulations run in low cost systems because we use the power of modern programmable GPUs. One can apply similar technology using GPU clusters and HPC for large scale problems. Such systems scale up almost linearly by using multiple GPUs.

We will discuss several steps in the process for simulating and visualizing large and varied crowds, in real time, for consumer-level computers and graphic cards (GPUs). Animating varied crowds using a diversity of models and animations (assets) is complex and costly. One needs models that are expensive if bought, take a long time to model, and consume too much memory and computing resources. We have developed methods for generating, simulating and animating crowds of varied aspect and a diversity of behaviors. Efficient simulations run in low cost systems because we use the power of modern programmable GPUs. One can apply similar technology using GPU clusters and HPC for large scale problems. Such systems scale up almost linearly by using multiple GPUs.

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Topics:
Media and Entertainment, Rendering & Ray Tracing, Real-Time Graphics, Visual Effects & Simulation
Type:
Talk
Event:
GTC Silicon Valley
Year:
2013
Session ID:
S3020
Streaming:
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