Power-Aware Characteristics of Matrix Operations on Multicores-Reference-Cited by-同舟云学术

Power-Aware Characteristics of Matrix Operations on Multicores

Published:2021-12-29 Issue: Volume: Page:1-22
ISSN:0883-9514
Container-title:Applied Artificial Intelligence
language:en
Short-container-title:Applied Artificial Intelligence

Author:

Konnurmath Guruprasad¹,Chickerur Satyadhyan²

Affiliation:

1. School of Computer Science and Engineering, K L E Technological University, Hubballi, Karnataka, India

2. Centre for High Performance Computing, K L E Technological University, Hubballi, Karnataka, India

Publisher

Informa UK Limited

Subject

Artificial Intelligence

Link

https://www.tandfonline.com/doi/pdf/10.1080/08839514.2021.1999013

Reference25 articles.

1. Analysis of DVFS Techniques for Improving the GPU Energy Efficiency

2. Bishwajit, D., V. Adhinarayanan, and W. Feng. 2018. GPU power prediction via ensemble machine learning for DVFS space exploration. ACMDigital library ISBN: 978-1-4503-5761-6.

3. Chien, S. W. D.,Stefano Markidis, Vyacheslav Olshevsky, Yaroslav Bulatov, Erwin Laure, Jeffrey S. Vetter. 2019. An evaluation of tensorflow performance in HPC applications, arXiv:1903.04364v1 [cs.DC] March 11, 2019

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