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GTC ON-DEMAND

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Abstract:

As Machine Learning advances for industrial applications, there will be an increasing need for it to scale productively. Similar to High Performance Computing, methods will be applied or eventually invented to allow for productive weak scaling, capacity and throughput. This will be the goal of our industry; although some will see faster implementation, others may take years. Therefore, in the meantime, a strong scaling and capability platform with tiers of ultra-high bandwidth, low latency interconnects and memory/storage classes will be needed. We will discuss such a system, such as Tokyo Tech's latest TSUBAME3.0 supercomputer, which is designed to achieve such strong scaling to over 2000 Pascal P100 processors, and together with its predecessor TSUBAME2.5 will provide the largest Machine Learning / AI capabilities in Japan.

As Machine Learning advances for industrial applications, there will be an increasing need for it to scale productively. Similar to High Performance Computing, methods will be applied or eventually invented to allow for productive weak scaling, capacity and throughput. This will be the goal of our industry; although some will see faster implementation, others may take years. Therefore, in the meantime, a strong scaling and capability platform with tiers of ultra-high bandwidth, low latency interconnects and memory/storage classes will be needed. We will discuss such a system, such as Tokyo Tech's latest TSUBAME3.0 supercomputer, which is designed to achieve such strong scaling to over 2000 Pascal P100 processors, and together with its predecessor TSUBAME2.5 will provide the largest Machine Learning / AI capabilities in Japan.

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Topics:
Artificial Intelligence and Deep Learning, HPC and Supercomputing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7813
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