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Here's my results: Testing new Tesla V100 on AWS. Fine-tuning VGG on DeepSent dataset for 10 epochs. GRID 520K (4GB) (baseline): * 780s/epoch @ minibatch 8 (

by eggie5 9y ago

Here's my results: Testing new Tesla V100 on AWS. Fine-tuning VGG on DeepSent dataset for 10 epochs. GRID 520K (4GB) (baseline): * 780s/epoch @ minibatch 8 (GPU saturated) V100(16Gb): * 30s/epoch @ minibatch 8 (GPU not saturated) * 6s/epoch @ minibatch 32 (GPU more saturated) * 6s/epoch @ minibatch 256 (GPU saturated)

dharma1 9y ago
Thanks! Curious how this would scale on the 8x or 16x instances
- eggie5 9y ago
  what do you mean? 8 or 16 GPUs? That's require changing the code to use distributed tensorflow...
  - dharma1 9y ago
    Yes exactly. The instances with 8 or 16 GPUs. Does the training time reduce linearly, is the GPU utilisation 100%, is it plug and play with TF