Theoretical analysis of classic algorithms on highly-threaded many-core GPUs

Lin Ma; Kunal Agrawal; Roger D. Chamberlain

doi:10.1145/2692916.2555285

Theoretical analysis of classic algorithms on highly-threaded many-core GPUs

Lin Ma
, Kunal Agrawal
, Roger D. Chamberlain

Department of Computer Science & Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

The Threaded many-core memory (TMM) model provides a framework to analyze the performance of algorithms on GPUs. Here, we investigate the effectiveness of the TMM model by analyzing algorithms for 3 classic problems - suffix tree/array for string matching, fast Fourier transform, and merge sort - under this model. Our findings indicate that the TMM model can explain and predict previously unexplained trends and artifacts in experimental data.

Original language	English
Pages (from-to)	391-392
Number of pages	2
Journal	ACM SIGPLAN Notices
Volume	49
Issue number	8
DOIs	https://doi.org/10.1145/2692916.2555285
State	Published - Feb 6 2014

Keywords

threaded many-core memory (TMM) model

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10.1145/2692916.2555285

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title = "Theoretical analysis of classic algorithms on highly-threaded many-core GPUs",

abstract = "The Threaded many-core memory (TMM) model provides a framework to analyze the performance of algorithms on GPUs. Here, we investigate the effectiveness of the TMM model by analyzing algorithms for 3 classic problems - suffix tree/array for string matching, fast Fourier transform, and merge sort - under this model. Our findings indicate that the TMM model can explain and predict previously unexplained trends and artifacts in experimental data.",

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Theoretical analysis of classic algorithms on highly-threaded many-core GPUs

Abstract

Keywords

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