MeterPU: a generic measurement abstraction API Enabling Energy-tuned Skeleton Backend Selection

Lu Li, Christoph Kessler

Research output: Contribution to journalArticlepeer-review

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.
Original languageEnglish
Number of pages16
JournalJournal of Supercomputing
Early online date24 Jun 2016
DOIs
Publication statusE-pub ahead of print - 24 Jun 2016

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