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GTC ON-DEMAND

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Abstract:
We'll discuss our team's work to determine how GPU virtualization, 5G, and edge computing, together with cutting-edge hardware and software solutions, can make cloud AR/VR a reality. Our talk will cover how 5G will shift computing and data storage to the cloud and enable new business models and commercial opportunities. We'll also talk about how 5G will enable high-resolution (4K or 8K) AR and VR, how these can revolutionize content consumption, and our role in making this possible.
We'll discuss our team's work to determine how GPU virtualization, 5G, and edge computing, together with cutting-edge hardware and software solutions, can make cloud AR/VR a reality. Our talk will cover how 5G will shift computing and data storage to the cloud and enable new business models and commercial opportunities. We'll also talk about how 5G will enable high-resolution (4K or 8K) AR and VR, how these can revolutionize content consumption, and our role in making this possible.  Back
 
Topics:
Virtual Reality & Augmented Reality, GPU Virtualization, 5G & Edge
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9620
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Abstract:

Learn about the plans of market leaders in streaming VR and AR content from the cloud in this panel discussion. From enterprise use cases to streaming VR to the 5G edge, panelists will describe the state-of-the-art and challenges to making XR truly mobile.

Learn about the plans of market leaders in streaming VR and AR content from the cloud in this panel discussion. From enterprise use cases to streaming VR to the 5G edge, panelists will describe the state-of-the-art and challenges to making XR truly mobile.

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Topics:
Virtual Reality & Augmented Reality
Type:
Panel
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9914
Streaming:
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Abstract:
Learn to develop a unique code base to deal with both NVIDIA GPU and Intel Xeon Phi by using directive-based programming approach (OpenACC and OpenMP4) . We carried out early experiment on ?, the GPU-Phi supercomputer of SJTU CCOE, with CAPS OpenACC compiler and HOMP, the OpenMP4-to-CUDA compiler based on Rose Compiler from LLNL. In this session we will show preliminary results of the evaluation with benchmarks and mini-apps, and then discuss different optimization methods applied, finally we will identify the strong, the weak, the missing features for OpenACC and OpenMP4 to achieve good performance portability on very different architectures.
Learn to develop a unique code base to deal with both NVIDIA GPU and Intel Xeon Phi by using directive-based programming approach (OpenACC and OpenMP4) . We carried out early experiment on ?, the GPU-Phi supercomputer of SJTU CCOE, with CAPS OpenACC compiler and HOMP, the OpenMP4-to-CUDA compiler based on Rose Compiler from LLNL. In this session we will show preliminary results of the evaluation with benchmarks and mini-apps, and then discuss different optimization methods applied, finally we will identify the strong, the weak, the missing features for OpenACC and OpenMP4 to achieve good performance portability on very different architectures.   Back
 
Topics:
Programming Languages, HPC and Supercomputing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2014
Session ID:
S4595
Streaming:
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Abstract:

SJTU-NS3D is an in-house CFD code co-developed by SJTU and COMAC for large civil airplane, solving 3D Reynolds Average Navier-Stokes (RANS) equations on structured grids by finite volume method, which could be used in designing wing model. In this talk, we will present the design and further optimization of CUDA version of SJTU-NS3D, and it achieves 20-fold speedup for standard M6 wing model and 37-fold speedup for wing model candidate from COMAC on single Fermi C2050.

SJTU-NS3D is an in-house CFD code co-developed by SJTU and COMAC for large civil airplane, solving 3D Reynolds Average Navier-Stokes (RANS) equations on structured grids by finite volume method, which could be used in designing wing model. In this talk, we will present the design and further optimization of CUDA version of SJTU-NS3D, and it achieves 20-fold speedup for standard M6 wing model and 37-fold speedup for wing model candidate from COMAC on single Fermi C2050.

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Topics:
Computational Fluid Dynamics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2012
Session ID:
S2251
Streaming:
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