The pace of AI adoption across diverse industries depends on maximizing data scientists’ productivity. NVIDIA releases optimized NGC containers every month with improved performance for deep learning frameworks and libraries, helping scientists maximize their potential. NVIDIA continuously invests in the full data science stack, including GPU architecture, systems, and software stacks.
]]>Today many servers contain 8 or more GPUs. In principle then, scaling an application from one to many GPUs should provide a tremendous performance boost. But in practice, this benefit can be difficult to obtain. There are two common culprits behind poor multi-GPU scaling. The first is that enough parallelism has not been exposed to efficiently saturate the processors. The second reason for poor…
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