A Scalable and Energy Efficient GPU Thread Map for m-Simplex Domains
Crist\'obal A. Navarro, Felipe A. Quezada, Benjamin Bustos, Nancy, Hitschfeld, Rolando Kindelan

TL;DR
This paper introduces a new GPU thread mapping technique for m-simplex domains that scales well with dimension, offering significant speedups and energy efficiency improvements over existing methods, especially in higher dimensions.
Contribution
The paper formulates a novel block-space map for m-simplex domains, analyzes its resource usage, and demonstrates its scalability and efficiency through extensive experiments.
Findings
Potential speedup up to 2x for 2-simplices and 6x for 3-simplices.
Achieves 1.2x to 2x speedup for 2-simplices, competitive with state-of-the-art.
Reaches up to 6x speedup for 3-simplices, outperforming existing approaches.
Abstract
This work proposes a new GPU thread map for -simplex domains, that scales its speedup with dimension and is energy efficient compared to other state of the art approaches. The main contributions of this work are i) the formulation of the new block-space map for regular orthogonal simplex domains, which is analyzed in terms of resource usage, and ii) the experimental evaluation in terms of speedup over a bounding box approach and energy efficiency as elements per second per Watt. Results from the analysis show that has a potential speedup of up to and for and -simplices, respectively. Experimental evaluation shows that is competitive for -simplices, reaching of speedup for different tests, which is on par with the fastest state of the art approaches.…
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Taxonomy
TopicsCellular Automata and Applications · Coding theory and cryptography · Interconnection Networks and Systems
