Abstract
In this paper, we propose a model for the energy consumption of the concurrent execution of three key dense matrix factorizations, with task parallelism leveraged via the Symmetric Multi-Processing Superscalar (SMPSs) runtime, on a multicore processor. Our model decomposes the power dissipation into the system, static and dynamic components, with the former two being estimated from basic, off-line experiments. The dynamic power, on the other hand, requires significantly more care, and we introduce a contention-aware model that accommodates for the variability of power consumption due to memory contention. Experimental results on an Intel Xeon E5504 processor with four cores, using an internal powermeter that samples the power drawn by the mainboard with a frequency of 1 KHz, show the reliability of the energy model for the Cholesky, LU, and QR factorizations on this platform.
