Transfer Learning Across Heterogeneous Features For Efficient Tensor Program Generation-Reference-Cited by-同舟云学术

Transfer Learning Across Heterogeneous Features For Efficient Tensor Program Generation

Published:2023-02-25 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2nd International Workshop on Extreme Heterogeneity Solutions
language:
Short-container-title:

Author:

Verma Gaurav¹^ORCID,Raskar Siddhisanket²^ORCID,Xie Zhen²^ORCID,Malik Abid M³^ORCID,Emani Murali²^ORCID,Chapman Barbara¹^ORCID

Affiliation:

1. Stony Brook University, Stony Brook, New York, USA

2. Argonne National Laboratory, Illinois, Chicago, USA

3. Brookhaven National Laboratory, Upton, New York, USA

Funder

Exascale Computing Project

National Science Foundation, USA

Argonne Leadership Computing Facility, DOE Office of Science User Facility

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3587278.3595644

Reference22 articles.

1. Byung Hoon Ahn , Prannoy Pilligundla , Amir Yazdanbakhsh , and Hadi Esmaeilzadeh . 2020 . Chameleon: Adaptive code optimization for expedited deep neural network compilation. arXiv preprint arXiv:2001.08743 (2020). Byung Hoon Ahn, Prannoy Pilligundla, Amir Yazdanbakhsh, and Hadi Esmaeilzadeh. 2020. Chameleon: Adaptive code optimization for expedited deep neural network compilation. arXiv preprint arXiv:2001.08743 (2020).

2. James Bradbury , Roy Frostig , Peter Hawkins , Matthew James Johnson , Chris Leary, Dougal Maclaurin, George Necula, Adam Paszke, Jake VanderPlas, Skye Wanderman-Milne, and Qiao Zhang. 2018 . JAX: composable transformations of Python +NumPy programs. http://github.com/google/jax James Bradbury, Roy Frostig, Peter Hawkins, Matthew James Johnson, Chris Leary, Dougal Maclaurin, George Necula, Adam Paszke, Jake VanderPlas, Skye Wanderman-Milne, and Qiao Zhang. 2018. JAX: composable transformations of Python+NumPy programs. http://github.com/google/jax

3. Tianqi Chen , Thierry Moreau , Ziheng Jiang , Lianmin Zheng , Eddie Yan , Haichen Shen , Meghan Cowan , Leyuan Wang , Yuwei Hu , Luis Ceze , 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.

4. Tianqi Chen , Lianmin Zheng , Eddie Yan , Ziheng Jiang , Thierry Moreau , Luis Ceze , Carlos Guestrin , and Arvind Krishnamurthy . 2018. Learning to optimize tensor programs. Advances in Neural Information Processing Systems 31 ( 2018 ). Tianqi Chen, Lianmin Zheng, Eddie Yan, Ziheng Jiang, Thierry Moreau, Luis Ceze, Carlos Guestrin, and Arvind Krishnamurthy. 2018. Learning to optimize tensor programs. Advances in Neural Information Processing Systems 31 (2018).

5. End-to-End Deep Learning of Optimization Heuristics

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