Integration of low-level sensors with TensorBoard
Abstract
Machine learning systems require substantial computational andenergy resources, particularly for training tasks. Profilers for these systems,such as the available on the TensorBoard tool for TensorFlow, provide insightinto performance hotspots and optimization opportunities. Nevertheless, suchtools typically lack energy profiling capabilities. In this work we present anpower dissipation profiling plugin for machine learning tasks based on low-levelIPMI sensors. The plugin is integrated with TensorBoard and demonstrated withan IBM POWER machine.
Keywords:
Performance measurements, evaluation and prediction
References
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Published
2021-05-06
How to Cite
MATSOUI, Julio Kiyoshi R.; FERNANDES, Matheus; WANNER, Lucas; RIGO, Sandro.
Integration of low-level sensors with TensorBoard. In: REGIONAL SCHOOL OF HIGH PERFORMANCE COMPUTING FROM SÃO PAULO (ERAD-SP), 12. , 2021, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 5-8.
DOI: https://doi.org/10.5753/eradsp.2021.16692.
