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Arithmetic Intensity Balancing Convolution for Hardware-aware Efficient Block Design
As deep learning advances, edge devices and lightweight neural networks are becoming more important.
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.
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