tensorflow / tensorflow/privacy
mnist_dpsgd_tutorial_vectorized Training slower on GPU
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Description
I'm running the vectorized tutorial (tf-gpu 1.14) and the per epoch training time on GPU (Nvidia Tesla M10) is slower than the non-vectorized implementation:
GPU
Vectorized : 203.55 seconds/epoch
Non-vectorized : 115 seconds/epoch
I was expecting to see better runtimes on GPU, but I am not sure why it's slower. Any help would be greatly appreciated.
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Research direction
Start by reproducing the vectorized and non-vectorized MNIST DPSGD tutorial runs with tf-gpu 1.14 on the reported Nvidia Tesla M10, using the per-epoch timings in the issue as the baseline. Compare the two tutorial implementations and their GPU execution behavior; done means explaining the runtime difference or identifying a reproducible performance fix.
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Assessment
- Tech stack
- python, tensorflow
- Domain
- machine-learning, performance
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100