AKG: automatic kernel generation for neural processing units using polyhedral transformations

Author:

Zhao Jie1ORCID,Li Bojie2,Nie Wang2,Geng Zhen2,Zhang Renwei2,Gao Xiong2,Cheng Bin2,Wu Chen3,Cheng Yun2,Li Zheng2,Di Peng2,Zhang Kun2,Jin Xuefeng2

Affiliation:

1. State Key Laboratory of Mathematical Engineering and Advanced Computing, China

2. Huawei Technologies, China

3. Huawei, China

Funder

National Natural Science Foundation of China

Publisher

ACM

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1. TensorMap: A Deep RL-Based Tensor Mapping Framework for Spatial Accelerators;IEEE Transactions on Computers;2024-08

2. Soter: Analytical Tensor-Architecture Modeling and Automatic Tensor Program Tuning for Spatial Accelerators;2024 ACM/IEEE 51st Annual International Symposium on Computer Architecture (ISCA);2024-06-29

3. A Survey of General-purpose Polyhedral Compilers;ACM Transactions on Architecture and Code Optimization;2024-06-22

4. Optimizing Dynamic-Shape Neural Networks on Accelerators via On-the-Fly Micro-Kernel Polymerization;Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2;2024-04-27

5. Optimizing Imperfectly-Nested Loop Mapping on CGRAs via Polyhedral-Guided Flattening;2024 Design, Automation & Test in Europe Conference & Exhibition (DATE);2024-03-25

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