Accelerating FaST-LMM for Epistasis Tests

Martínez, Héctor; Barrachina, Sergio; Castillo, Maribel; Quintana-Ortí, Enrique S.; Rambla De Argila, Jordi; Ferré, Xavier; Navarro, Arcadi

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Author

Martínez, Héctor

Barrachina, Sergio

Castillo, Maribel

Quintana-Ortí, Enrique S.

Rambla De Argila, Jordi

Ferré, Xavier

Navarro, Arcadi

Publisher

Springer Nature

Date

2017

Subject

Epistasis
FaST-LMM
High-performance computing
Multithreaded parallelism
Graphics processors

Abstract

We introduce an enhanced version of FaST-LMM that main- tains the sensitivity of this software when applied to identify epistasis interactions while delivering an acceleration factor that is close to 7.5× on a server equipped with a state-of-the-art graphics coprocessor. This performance boost is obtained from the combined eﬀects of integrating a dictionary for faster storage of the test results; a re-organization of the original FaST-LMM Python code; and oﬀ-loading of compute-intensive parts to the graphics accelerator.

URI

http://hdl.handle.net/10396/32098

Fuente

Martínez, H. et al. (2017). Accelerating FaST-LMM for Epistasis Tests. In: Ibrahim, S., Choo, KK., Yan, Z., Pedrycz, W. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2017. Lecture Notes in Computer Science(), vol 10393. Springer, Cham. https://doi.org/10.1007/978-3-319-65482-9_40

Versión del Editor

https://doi.org/10.1007/978-3-319-65482-9_40