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TF not compatible with AWS GPU instances? #142

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nbenhaim opened this issue Nov 11, 2015 · 3 comments
Closed

TF not compatible with AWS GPU instances? #142

nbenhaim opened this issue Nov 11, 2015 · 3 comments

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@nbenhaim
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It seems like Google Compute Engine doesn't even have gpu instances, and AWS GPU instance isn't supported because it requires >= 3.5 cuda compute capability. Is this correct?
@ebrevdo
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ebrevdo commented Nov 11, 2015

This is correct. We currently do not support AWS GPU instances because of their 3.0 cuda compute capability. You can try disabling that requirement in the source code and seeing if it works for you.

@anjishnu
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Is there any plan to support them, i.e. does the tensorflow source actually utilize the new features in cuda 3.5 capability?

@vrv
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vrv commented Nov 11, 2015

zheng-xq is working on adding configurable support to it.

For every compute capability you add, the compile time and binary size increases significantly, so we're trying to find a solution.

In any case, thanks for the report -- de-duping with #25.

@vrv vrv closed this as completed Nov 11, 2015
hristo-vrigazov pushed a commit to hristo-vrigazov/tensorflow that referenced this issue Oct 1, 2019
@bondhugula @tensorflower-gardener
update layout map examples in doc, drop stale ones
eaa846c 
- add more examples for affine layout maps showing various use
  cases

- affine map range sizes were removed from code, but examples in
  LangRef weren't updated

Signed-off-by: Uday Bondhugula <uday@polymagelabs.com>

Closes tensorflow#142

COPYBARA_INTEGRATE_REVIEW=tensorflow/mlir#142 from bondhugula:doc 3291a8784bc69883f7a7cead21445fc8118aaad2
PiperOrigin-RevId: 270548991
@chengdianxuezi chengdianxuezi mentioned this issue Nov 1, 2019
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5 participants
@vrv @teamdandelion @ebrevdo @anjishnu @nbenhaim