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We analyze power dissipation and energy consumption during the execution of high-performance dense linear algebra kernels on multi-core processors. On top of this analysis, we propose and evaluate several strategies to adapt concurrency throttling and the voltage-frequency setting in order to obtain an energy-efficient execution of LAPACK's routine dsytrd. Our strategies take into account the differences between the memory-bound and CPU-bound kernels that govern this routine, and whether problem data fits into the processor's last level cache.
dense linear algebra; eigenvalue problems; concurrency throttling (ct); dynamic voltage-frequency scaling (dvfs); energy; high performance