Comments on: One Deep Learning Benchmark to Rule Them All https://www.nextplatform.com/2018/08/30/one-deep-learning-benchmark-to-rule-them-all/ In-depth coverage of high-end computing at large enterprises, supercomputing centers, hyperscale data centers, and public clouds. Wed, 12 Sep 2018 22:30:24 +0000 hourly 1 https://wordpress.org/?v=6.5.5 By: OranjeeGeneral https://www.nextplatform.com/2018/08/30/one-deep-learning-benchmark-to-rule-them-all/#comment-103681 Sun, 02 Sep 2018 16:41:14 +0000 http://www.nextplatform.com/?p=38285#comment-103681 In reply to Jan Tångring.

No it is not depends largely on batch size and the framework used. That’s why I think there just too many variables in this benchmark which makes the numbers non comparable and runs the whole benchmark useless unless I am missing something.

For hardware best would be to stick to just interference as there you could use a pre-defined network (in ONNX) format

]]> By: Jan Tångring https://www.nextplatform.com/2018/08/30/one-deep-learning-benchmark-to-rule-them-all/#comment-103495 Thu, 30 Aug 2018 19:54:19 +0000 http://www.nextplatform.com/?p=38285#comment-103495 Is training a deterministic process? It’s not, right? How will the benchmark handle that? Will all runs even converge? And how do you define convergence?

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