awesome-tensor-compilers
Enrichment pendingA list of awesome compiler projects and papers for tensor computation and deep learning.
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Created Jun 18, 2020
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Overview
A list of awesome compiler projects and papers for tensor computation and deep learning.
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Cost Model
- TLP: A Deep Learning-based Cost Model for Tensor Program Tuning by Yi Zhai et al., ASPLOS 2023
- An Asymptotic Cost Model for Autoscheduling Sparse Tensor Programs by Peter Ahrens et al., PLDI 2022
- TenSet: A Large-scale Program Performance Dataset for Learned Tensor Compilers by Lianmin Zheng et al., NeurIPS 2021
- A Deep Learning Based Cost Model for Automatic Code Optimization by Riyadh Baghdadi et al., MLSys 2021
- A Learned Performance Model for the Tensor Processing Unit by Samuel J. Kaufman et al., MLSys 2021
- DYNATUNE: Dynamic Tensor Program Optimization in Deep Neural Network Compilation by Minjia Zhang et al., ICLR 2021
- MetaTune: Meta-Learning Based Cost Model for Fast and Efficient Auto-tuning Frameworks by Jaehun Ryu et al., arxiv 2021
- Expedited Tensor Program Compilation Based on LightGBM by Gonghan Liu1 et al., JPCS 2021