BaCO: A Fast and Portable Bayesian Compiler Optimization Framework-Reference-Cited by-同舟云学术

BaCO: A Fast and Portable Bayesian Compiler Optimization Framework

Published:2023-03-25 Issue: Volume: Page:
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Container-title:Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 4
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Author:

Hellsten Erik Orm¹^ORCID,Souza Artur²^ORCID,Lenfers Johannes³^ORCID,Lacouture Rubens⁴^ORCID,Hsu Olivia⁵^ORCID,Ejjeh Adel⁶^ORCID,Kjolstad Fredrik⁵^ORCID,Steuwer Michel⁷^ORCID,Olukotun Kunle⁵^ORCID,Nardi Luigi⁸^ORCID

Affiliation:

1. Lund University, Lund, Sweden

2. Federal University of Minas Gerais, Belo Horizonte, Brazil

3. University of Münster, Münster, Germany

4. Stanford University, San Francisco, USA

5. Stanford University, San Francisco, United States of America

6. University of Illinois at Urbana-Champaign, Illinois, United States of America

7. University of Edinburgh, Edinburgh, Scotland Uk

8. Lund University - Stanford University, Lund, Sweden

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3623278.3624770

Reference65 articles.

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2. Jason Ansel, Shoaib Kamil, Kalyan Veeramachaneni, Jonathan Ragan-Kelley, Jeffrey Bosboom, Una-May O'Reilly, and Saman Amarasinghe. OpenTuner: An extensible framework for program autotuning. In International Conference on Parallel Architectures and Compilation Techniques (PACT), 2014.

3. The GPyOpt authors. GPyOpt: A bayesian optimization framework in python. http://github.com/SheffieldML/GPyOpt 2016.

4. Autotuning in High-Performance Computing Applications

5. Autotuning high-level synthesis for FPGAs using OpenTuner and LegUp

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