Utilizing ensemble learning for performance and power modeling and improvement of parallel cancer deep learning CANDLE benchmarks-Reference-Cited by-同舟云学术

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Utilizing ensemble learning for performance and power modeling and improvement of parallel cancer deep learning CANDLE benchmarks

Published:2021-07-22 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,Taylor Valerie¹

Affiliation:

1. Mathematics & Computer Science Division, Argonne National Laboratory The University of Chicago Lemont Illinois USA

Funder

National Science Foundation

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.6516

Reference52 articles.

1. SinghK BhadhauriaM McKeeS. A. Real time power estimation and thread scheduling via performance counters. ACM SIGARCH Computer Architecture News Volume 37 Issue 2 May 2009 pp 46–55.

2. Complete System Power Estimation Using Processor Performance Events

3. A Study on the Use of Performance Counters to Estimate Power in Microprocessors

4. MayerZ. A brief Introduction to caretEnsemble;2016.

5. Machine Learning

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Performance and power modeling and prediction using MuMMI and 10 machine learning methods;Concurrency and Computation: Practice and Experience;2022-08-05

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