Autotuning PolyBench benchmarks with LLVM Clang/Polly loop optimization pragmas using Bayesian optimization-Reference-Cited by-同舟云学术

Autotuning PolyBench benchmarks with LLVM Clang/Polly loop optimization pragmas using Bayesian optimization

Published:2021-11-08 Issue: Volume: Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat Pract Exper

Author:

Wu Xingfu¹^ORCID,Kruse Michael²,Balaprakash Prasanna¹,Finkel Hal²,Hovland Paul¹,Taylor Valerie¹,Hall Mary³

Affiliation:

1. Mathematics & Computer Science Division Argonne National Laboratory Lemont Illinois USA

2. Argonne Leadership Computing Facility Argonne National Laboratory Lemont Illinois USA

3. Department of Computer Science University of Utah Salt Lake City Utah USA

Funder

U.S. Department of Energy

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.6683

Reference54 articles.

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3. Automatic performance analysis with periscope

4. TiwariA HollingsworthJK.Online adaptive code generation and tuning. Proceedings of the 2011 IEEE International Parallel & Distributed Processing Symposium (IPDPS'11); 2011.

5. BalaprakashP GramacyRB WildSM.Active‐learning‐based surrogate models for empirical performance running. Proceedings of the 2013 IEEE International Conference on Cluster Computing (CLUSTER'13); 2013.

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