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GTC ON-DEMAND

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Abstract:
GPUDirect Storage is a new technology that enables a direct data path between storage devices and the GPU. Eliminating unnecessary memory copies through the CPU, boosts bandwidth, lowers latency, and reduced CPU and GPU overhead. It is the easiest way to scale performance when IO to the GPU is a bottleneck. In this talk well explain the technology its benefits and explain the end to end use cases. We will also introduce distributed file systems partners supporting GPUDirect Storage.
GPUDirect Storage is a new technology that enables a direct data path between storage devices and the GPU. Eliminating unnecessary memory copies through the CPU, boosts bandwidth, lowers latency, and reduced CPU and GPU overhead. It is the easiest way to scale performance when IO to the GPU is a bottleneck. In this talk well explain the technology its benefits and explain the end to end use cases. We will also introduce distributed file systems partners supporting GPUDirect Storage.  Back
 
Topics:
HPC and Supercomputing
Type:
Talk
Event:
Supercomputing
Year:
2019
Session ID:
SC1922
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Abstract:
NVIDIA offers several containerized applications in HPC, visualization, and deep learning. We have also enabled a broad array of contain-related technologies for GPUs with upstreamed improvements to community projects and with tools that are seeing broad interest and adoption. In addition, NVIDIA is a catalyst for the broader community in enumerating key technical challenges for developers, admins and end users, and is helping to identify gaps and drive them to closure. Our talk describes NVIDIA's new developments and upcoming efforts. We'll detail progress in the most important technical areas, including multi-node containers, security, and scheduling frameworks. We'll also offer highlights of the breadth and depth of interactions across the HPC community that are making the latest, highly-quality HPC applications available to platforms that include GPUs.
NVIDIA offers several containerized applications in HPC, visualization, and deep learning. We have also enabled a broad array of contain-related technologies for GPUs with upstreamed improvements to community projects and with tools that are seeing broad interest and adoption. In addition, NVIDIA is a catalyst for the broader community in enumerating key technical challenges for developers, admins and end users, and is helping to identify gaps and drive them to closure. Our talk describes NVIDIA's new developments and upcoming efforts. We'll detail progress in the most important technical areas, including multi-node containers, security, and scheduling frameworks. We'll also offer highlights of the breadth and depth of interactions across the HPC community that are making the latest, highly-quality HPC applications available to platforms that include GPUs.  Back
 
Topics:
Data Center & Cloud Infrastructure, HPC and AI
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9525
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Abstract:

NVIDIA offers several containerized applications in HPC, visualization, and deep learning. We have also enabled a broad array of contain-related technologies for GPU with upstreamed improvements to community projects and with tools that are seeing broad interest and adoption. Furthermore, NVIDIA is acting as a catalyst for the broader community in enumerating key technical challenges for developers, admins and end users, and is helping to identify gaps and drive them to closure. This talk describes NVIDIA new developments and upcoming efforts. It outlines progress in the most important technical areas, including multi-node containers, security, and scheduling frameworks. It highlights the breadth and depth of interactions across the HPC community that are making the latest, highly-quality HPC applications available to platforms that include GPUs. 

NVIDIA offers several containerized applications in HPC, visualization, and deep learning. We have also enabled a broad array of contain-related technologies for GPU with upstreamed improvements to community projects and with tools that are seeing broad interest and adoption. Furthermore, NVIDIA is acting as a catalyst for the broader community in enumerating key technical challenges for developers, admins and end users, and is helping to identify gaps and drive them to closure. This talk describes NVIDIA new developments and upcoming efforts. It outlines progress in the most important technical areas, including multi-node containers, security, and scheduling frameworks. It highlights the breadth and depth of interactions across the HPC community that are making the latest, highly-quality HPC applications available to platforms that include GPUs. 

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Topics:
Application Design & Porting Techniques
Type:
Talk
Event:
Supercomputing
Year:
2018
Session ID:
SC1821
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