MeterPU: a generic measurement abstraction API

Enabling energy-tuned skeleton backend selection
Article

DOI: 10.1007/s11227-016-1792-x

Cite this article as:
Li, L. & Kessler, C. J Supercomput (2016). doi:10.1007/s11227-016-1792-x

Abstract

We present MeterPU, an easy-to-use, generic and low-overhead abstraction API for taking measurements of various metrics (time, energy) on different hardware components (e.g., CPU, DRAM, GPU) in a heterogeneous computer system, using pluggable platform-specific measurement implementations behind a common interface in C++. We show that with MeterPU, not only legacy (time) optimization frameworks, such as autotuned skeleton back-end selection, can be easily retargeted for energy optimization, but also switching between measurement metrics or techniques for arbitrary code sections now becomes trivial. We apply MeterPU to implement the first energy-tunable skeleton programming framework, based on the SkePU skeleton programming library.

Keywords

MeterPU Measurement abstraction API GPU Performance measurement Energy measurement Auto-tuning Skeleton programming 

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.IDA, Linköping UniversityLinköpingSweden

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