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Benchmarking parallel programming for single-board computers
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AI
DOI：10.1016/j.future.2024.07.003.png)
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Abstract
En 中文
Within the computing continuum, SBCs (single-board computers) are essential in the Edge and Fog, with many featuring multiple processing cores and GPU accelerators. In this way, parallel computing plays a crucial role in enabling the full computational potential of SBCs. However, selecting the best-suited solution in this context is inherently complex due to the intricate interplay between PPI (parallel programming interface) strategies, SBC architectural characteristics, and application characteristics and constraints. To our knowledge, no solution presents a combined discussion of these three aspects. To tackle this problem, this article aims to provide a benchmark of the best-suited parallelism PPIs given a set of hardware and application characteristics and requirements. Compared to existing benchmarks, we introduce new metrics, additional applications, various parallelism interfaces, and extra hardware devices. Therefore, our contributions are the methodology to benchmark parallelism on SBCs and the characterization of the best-performing parallelism PPIs and strategies for given situations. We are confident that parallel computing will be mainstream to process edge and fog computing; thus, our solution provides the first insights regarding what kind of application and parallel programming interface is the most suited for a particular SBC hardware.
Keywords:
Programming models
Parallel computing
Edge computing
Performance analysis
Computing continuum
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