2024-03-29T09:10:54Zhttps://repositori.uji.es/oai/requestoai:repositori.uji.es:10234/1775622022-11-10T18:55:47Zcom_10234_7036com_10234_9col_10234_8620
00925njm 22002777a 4500
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Aliaga Estellés, José Ignacio
author
Barreda Vayá, Maria
author
Castaño, Asunción
author
2018
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.
ALIAGA, José I.; BARREDA, María; CASTAÑO, Asunción. Energy‐aware strategies for task‐parallel sparse linear system solvers. Concurrency and Computation: Practice and Experience, 2018, p. e4633.
1532-0626
1532-0634
http://hdl.handle.net/10234/177562
https://doi.org/10.1002/cpe.4633
DVFS
energy efficiency
ILUPACK
power-saving states
preconditioned Conjugate Gradient
sparse linear systems
task-parallelism
Energy‐aware strategies for task‐parallel sparse linear system solvers