DEEP LEARNING BENCHMARKS ON SUPERMICRO'S 4U 8 GPU SYSTEMBASED ONDUAL 3RDGEN AMD EPYC™ PROCESSORS White Paper
■Artificial Intelligence is being adopted in various industries worldwide. The choice of systems to perform these complex tasks is critical and requires understanding how the different system components act together. A series of benchmarks have been created that allow those who evaluate systems and architectures to determine which combination of CPUs and GPUs are the best fit for their workloads.
■AI workloads require optimized systems and need to incorporate the proper hardware and tuning the software to deliver maximum performance at a given price point. A solution that provides value to end-users consists of the choice of CPUs, GPUs, and the proper software stack. Various numbers of cores, communication latency between cores, GHz, and which generation of CPU architectures can influence benchmark performance of real-world AI applications.
■A comparison will be run for this benchmarkthat compares 2nd Gen AMD EPYC™ processors to 3rd Gen AMD EPYC processors. AMD provides a wide range of processors with different numbers of cores and speed levels. Any AI/DL/ML application will depend heavily on the GPUs selected. Supermicro has run benchmarks that use different CPU generations and NVIDIA V100 and A100 GPUs. The CPU controls the management and assignment of work to the GPUs, while the GPU does the heavy liftingof transforming, loading, and analyzing the data. This is the training phase of AI deep learning, as well as inferencing.
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Please see the document for details |
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March 2021 |
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