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28 lines
1.0 KiB
28 lines
1.0 KiB
Notes on Floating Point Precisions in Deep Learning Computations
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ECCV 2020 Tutorial on Accelerating Computer Vision with Mixed Precision
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https://nvlabs.github.io/eccv2020-mixed-precision-tutorial/
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Topics of the tutorial:
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* Training Neural Networks with Tensor Cores
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* PyTorch Performance Tuning Guide
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* Mixed Precision Training for Conditional GANs
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* Mixed Precision Training for FAZE: Few-shot Adaptive Gaze Estimation
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* Mixed Precision Training for Video Synthesis
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* Mixed Precision Training for Convolutional Tensor-Train LSTM
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* Mixed Precision Training for 3D Medical Image Analysis
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Has PDF of the slides and the videos.
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Q&A:
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**What's the difference between FP32 and TF32 modes?**
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FP32 cores perform scalar instructions. TF32 is a Tensor Core mode,
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which performs matrix instructions - they are 8-16x faster and more
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energy efficient. Both take FP32 as inputs. TF32 mode also rounds
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those inputs to TF32.
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