Nvidia highlights Intel Deep Learning benchmark mistakes

At the ISC High Performance conference back in June, which focuses upon HPC developments, Intel published a press deck (PDF) trumpeting the appeal of its Knights Landing Xeon Phi processors. Among the compelling qualities of the Xeon Phi, according to Intel, was its use for Deep Learning, and it was shown in the presentation slides to be a top performer at essential ‘training’ tasks. I have reproduced the slide I am referring to directly below. The key claims of the slide, and what its graphs try to make immediately clear, is that Xeon Phi outperforms GPUs for deep learning training in three major ways: Xeon Phi is 2.3x faster in training than GPUs Xeon Phi offers 38% better scaling that GPUs across nodes Xeon Phi delivers strong scaling to 128…


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