Accelerate DNN Performance with Sparse Matrix Compression in Halide-Reference-Cited by-同舟云学术

Accelerate DNN Performance with Sparse Matrix Compression in Halide

Published:2019-08-05 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 48th International Conference on Parallel Processing: Workshops
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Author:

Lee Chao-Lin¹,Chao Chen-Ting¹,Lee Jenq-Kuen¹,Hung Ming-Yu²,Huang Chung-Wen²

Affiliation:

1. National Tsing Hua University, Hsinchu, Taiwan

2. MediaTek Inc., Hsinchu, Taiwan

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3339186.3339194

Reference12 articles.

1. Support and optimization for parallel sparse programs with array intrinsics of Fortran 90

2. Tianqi Chen Thierry Moreau Ziheng Jiang Lianmin Zheng Eddie Yan Haichen Shen Meghan Cowan Leyuan Wang Yuwei Hu Luis Ceze etal 2018. {TVM}: An automated end-to-end optimizing compiler for deep learning. In 13th {USENIX} Symposium on Operating Systems Design and Implementation ({OSDI} 18). 578--594. Tianqi Chen Thierry Moreau Ziheng Jiang Lianmin Zheng Eddie Yan Haichen Shen Meghan Cowan Leyuan Wang Yuwei Hu Luis Ceze et al. 2018. {TVM}: An automated end-to-end optimizing compiler for deep learning. In 13th {USENIX} Symposium on Operating Systems Design and Implementation ({OSDI} 18). 578--594.

3. MIT CSAIL. 2019. Halide - a language for fast portable computation on images and tensors. https://halide-lang.org/ MIT CSAIL. 2019. Halide - a language for fast portable computation on images and tensors. https://halide-lang.org/

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