Deep Learning on FPGAs: Past, Present, and Future — HN submission

Fri, 25 May 2018 11:34:45 GMT

Deep Learning on FPGAs: Past, Present, and Future

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Deep Learning on FPGAs: Past, Present, and Future — mentioned by nl

Thu, 01 Dec 2016 09:44:04 GMT

No, but they do use less power: To the best of our knowledge, state-of-the-art performance for forward propagation of CNNs on FPGAs was achieved by a team at Microsoft. Ovtcharov et al. have reported a throughput of 134 images/second on the ImageNet 1K dataset [28], which amounts to roughly 3x the throughput of the next closest competitor, while operating at 25 W on a Stratix V D5 [30]. This performance is projected to increase by using top-of-the-line FPGAs, with an estimated through- put of roughly 233 images/second while consuming roughly the same power on an Arria 10 GX1150. This is com…

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Deep Learning on FPGAs: Past, Present, and Future · HackerPapers discussions

Deep Learning on FPGAs: Past, Present, and Future — HN submission

Deep Learning on FPGAs: Past, Present, and Future — mentioned by nl