Benchmark Analysis of Representative Deep Neural Network Architectures — mentioned by nl

Tue, 19 Mar 2019 03:15:39 GMT

Cheaper than the $150 Google TPU Dev Board, and looks like it can do training as well as inference. Training is a slight win (although it's going to be too slow for anything useful really). But it looks like the TPU will outperform this somewhat for inference. The 256 core Jetson (this has 128 cores) could run MobileNet-v2 at between 12 and 20 ms per image (depending on batch size)[1], while the USB TPU adapter takes 2.3ms per image [2] Also, doesn't require you to send your model to their company. Nor does the TPU dev board. [1] https://arxiv.org/pdf/1810.00736.pdf (see table 1) [2]…

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Benchmark Analysis of Representative Deep Neural Network Architectures · HackerPapers discussions

Benchmark Analysis of Representative Deep Neural Network Architectures — mentioned by nl