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Abstract:
Learn how we explore the feasibility of porting YALES2 on GPU. YALES2 is an HPC application for turbulent combustion modeling from primary atomization to pollutant prediction on massive complex meshes. It runs over thousands of CPU cores solving several billions element meshes through MPI+OpenMP programming. The work presented here is focusing on a preliminary feasibility study of GPU porting. In this session we will describe: a methodology for porting a large code to GPU; the choices that have been made regarding the different constraints; the performance results. We will also present the final benchmarks run across several platforms form classic Intel+Kepler cluster at ROMEO HPC Center (University of Reims, France) to prototypes with IBM Power8+Pascal at IDRIS (CNRS, France).
Learn how we explore the feasibility of porting YALES2 on GPU. YALES2 is an HPC application for turbulent combustion modeling from primary atomization to pollutant prediction on massive complex meshes. It runs over thousands of CPU cores solving several billions element meshes through MPI+OpenMP programming. The work presented here is focusing on a preliminary feasibility study of GPU porting. In this session we will describe: a methodology for porting a large code to GPU; the choices that have been made regarding the different constraints; the performance results. We will also present the final benchmarks run across several platforms form classic Intel+Kepler cluster at ROMEO HPC Center (University of Reims, France) to prototypes with IBM Power8+Pascal at IDRIS (CNRS, France).  Back
 
Topics:
Computational Fluid Dynamics, HPC and AI
Type:
Talk
Event:
GTC Europe
Year:
2017
Session ID:
23254
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Abstract:
Considering the technical features of the GPUs and their current limitations, this poster presents a generic scheme for combinatorial problems resolution on multiGPU clusters. The method was tested on the Langford problem, which is an extremely irregular combinatorial problem. It proved efficient although the problem is not well suited for vectorized computation.
Considering the technical features of the GPUs and their current limitations, this poster presents a generic scheme for combinatorial problems resolution on multiGPU clusters. The method was tested on the Langford problem, which is an extremely irregular combinatorial problem. It proved efficient although the problem is not well suited for vectorized computation.  Back
 
Topics:
Tools & Libraries, HPC and Supercomputing
Type:
Poster
Event:
GTC Silicon Valley
Year:
2015
Session ID:
P5330
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Abstract:

PSA Peugeot Citroen in partnership with Reims University, RTT and Barco will show a car model in Real Time Full GI using the Romeo supercomputer based in Reims, France equipped with 260 Tesla K20s. The car model will be loaded into RTT DeltaGen which will be connected to Reims through a remote display to leverage the horse power of the GPU Cluster. Tapping into this power on demand allows Peugeot to achieve stunning photorealistic results in real time, as if the real vehicle was right in front of them. With this, design changes for materials and colors can be visualized instantly and decisions can be made faster.

PSA Peugeot Citroen in partnership with Reims University, RTT and Barco will show a car model in Real Time Full GI using the Romeo supercomputer based in Reims, France equipped with 260 Tesla K20s. The car model will be loaded into RTT DeltaGen which will be connected to Reims through a remote display to leverage the horse power of the GPU Cluster. Tapping into this power on demand allows Peugeot to achieve stunning photorealistic results in real time, as if the real vehicle was right in front of them. With this, design changes for materials and colors can be visualized instantly and decisions can be made faster.

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Topics:
Digital Manufacturing, Autonomous Vehicles, Product & Building Design, Rendering & Ray Tracing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2014
Session ID:
S4845
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