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Energy‐aware strategies for task‐parallel sparse linear system solvers
Author(s) -
Aliaga José I.,
Barreda María,
Castaño Asunción
Publication year - 2018
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.4633
Subject(s) - computer science , solver , parallel computing , xeon , leverage (statistics) , conjugate gradient method , computation , efficient energy use , xeon phi , task (project management) , energy (signal processing) , energy consumption , computational science , algorithm , mathematics , artificial intelligence , statistics , engineering , ecology , management , electrical engineering , economics , biology , programming language
Summary We present several energy‐aware strategies to improve the energy efficiency of a task‐parallel preconditioned Conjugate Gradient (PCG) iterative solver on a Haswell‐EP Intel Xeon. These techniques leverage the power‐saving states of the processor, promoting the hardware into a more energy‐efficient C‐state and modifying the CPU frequency (P‐states of the processors) of some operations of the PCG. We demonstrate that the application of these strategies during the main operations of the iterative solver can reduce its energy consumption considerably, especially for memory‐bound computations.