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Automating HPC Model Selection on Edge Devices
SessionPoster Reception
DescriptionThe increasing demand for processing power on resource-constrained edge devices necessitate efficient techniques for optimizing High Performance Computing (HPC) applications. We propose HPEE (HPC Parameter Exploration on Edge), a novel approach that formulates the parameter search space problem as a pure exploration multi-armed bandit (MAB) technique. By efficiently exploring the search space using the MAB framework, we achieve significant performance improvements, while respecting the limited computational resources of edge devices. Experimental results, based on HPC application, demonstrate the effectiveness of our approach in optimizing parameter search on edge devices, offering a promising solution for enhancing HPC performance in resource-constrained environments.
Event Type
ACM Student Research Competition: Graduate Poster
ACM Student Research Competition: Undergraduate Poster
Doctoral Showcase
Posters
Research Posters
Scientific Visualization & Data Analytics Showcase
TimeTuesday, 14 November 20235:15pm - 7pm MST
LocationDEF Concourse
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