Optimizing Block-Sparse Matrix Multiplications on CUDA with TVM

• URL: http://arxiv.org/abs/2007.13055v1
• Date: Sun, 26 Jul 2020 04:50:51 GMT
• Title: Optimizing Block-Sparse Matrix Multiplications on CUDA with TVM
• Authors: Zijing Gu
• Abstract summary: We leveraged TVM, a deep learning compiler, to explore the schedule space of the operation and generate efficient code. Our cross-thread reduction based implementation achieved competitive or better performance compared with other state-of-the-art frameworks.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We implemented and optimized matrix multiplications between dense and block-sparse matrices on CUDA. We leveraged TVM, a deep learning compiler, to explore the schedule space of the operation and generate efficient CUDA code. With the automatic parameter tuning in TVM, our cross-thread reduction based implementation achieved competitive or better performance compared with other state-of-the-art frameworks.

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