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Powersched(Hawk): Difference between revisions
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Powersched proposes a reliable, efficient, and transparent mechanism to keep a HPC system under a power cap. The tool aims to increase the energy efficiency of available resources by enabling power capping based on an application-specific, energy-optimized runtime environment. The power capping is governed by the GSS-optimization of a given metric (a variant of the Energy-Delay-Product) and will adapt to different application phases. Depending on the job characteristic we aim for an improvement in energy efficiency of order 20% with a moderate performance impact (or gain) of order 5%. | Powersched proposes a reliable, efficient, and transparent mechanism to keep a HPC system under a power cap. The tool aims to increase the energy efficiency of available resources by enabling power capping based on an application-specific, energy-optimized runtime environment. The power capping is governed by the GSS-optimization of a given metric (a variant of the Energy-Delay-Product) and will adapt to different application phases. Depending on the job characteristic we aim for an improvement in energy efficiency of order 20% with a moderate performance impact (or gain) of order 5%. | ||
A summary is included below. | |||
===== Golden Section Search (GSS) ===== | |||
===== Golden Section Search (GSS) ====== | |||
[[File:GSS.png|689px]] | [[File:GSS.png|689px]] | ||
Dynamic power capping for changing application phases. | Dynamic power capping for changing application phases. | ||
==== Overview and Architecture ==== | ==== Overview and Architecture ==== | ||
[[Media:HLRS_Workshop_Powersched_GSS.pdf]] | [[Media:HLRS_Workshop_Powersched_GSS.pdf]] | ||
Revision as of 15:59, 9 January 2024
Power Management (Powersched)
Powersched
Powersched proposes a reliable, efficient, and transparent mechanism to keep a HPC system under a power cap. The tool aims to increase the energy efficiency of available resources by enabling power capping based on an application-specific, energy-optimized runtime environment. The power capping is governed by the GSS-optimization of a given metric (a variant of the Energy-Delay-Product) and will adapt to different application phases. Depending on the job characteristic we aim for an improvement in energy efficiency of order 20% with a moderate performance impact (or gain) of order 5%.
A summary is included below.
Golden Section Search (GSS) =
Dynamic power capping for changing application phases.