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Automatic Network Adaptation for Ultra-Low Uniform-Precision Quantization
Uniform-precision neural network quantization has gained popularity since it simplifies densely packed arithmetic unit for high computing capability.
Learning from distinctive candidates to optimize reduced-precision convolution program on tensor cores
In this method, we devise a search space that explores the thread tile and warp sizes to increase the data reuse despite a large matrix operand of reduced-precision MMA.
Uniform-Precision Neural Network Quantization via Neural Channel Expansion
Uniform-precision neural network quantization has gained popularity thanks to its simple arithmetic unit densely packed for high computing capability.
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