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Habitat - A Runtime-Based Computational Performance Predictor for Deep Neural Network Training
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- 1 Intro
- 2 What this talk is about The problem: • Many GPUs available for deep neural network (DNN) training . Each has a different cost and performance
- 3 A Cambrian explosion in hardware for training
- 4 Choosing a GPU: The paradox of choice
- 5 Key observations • Deep learning users may already have an existing GPU
- 6 Habitat: A runtime-based performance predictor
- 7 One last wrinkle: Kernel-varying operations Wave scaling assumes the same kernel is used across GPUS
- 8 Evaluation
- 9 How accurate is Habitat?
- 10 Rent a GPU in the cloud? Scenario: Want to train GNMT, have access to a P4000. Which cloud GPU to use, if any?
- 11 Key takeaways . DNN computation is special (repetitive), enabling new analysis opportunities
