enabling fair pricing on high performance computer systems with node sharing

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ID: 216213
2014
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Abstract
Co-location, where multiple jobs share compute nodes in large-scale HPC systems, has been shown to increase aggregate throughput and energy efficiency by 10–20%. However, system operators disallow co-location due to fair-pricing concerns, i.e., a pricing mechanism that considers performance interference from co-running jobs. In the current pricing model, application execution time determines the price, which results in unfair prices paid by the minority of users whose jobs suffer from co-location. This paper presents POPPA, a runtime system that enables fair pricing by delivering precise online interference detection and facilitates the adoption of supercomputers with co-locations. POPPA leverages a novel shutter mechanism – a cyclic, fine-grained interference sampling mechanism to accurately deduce the interference between co-runners – to provide unbiased pricing of jobs that share nodes. POPPA is able to quantify inter-application interference within 4% mean absolute error on a variety of co-located benchmark and real scientific workloads.
Reference Key
breslow2014scientificenabling Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Alex D. Breslow, Ananta Tiwari, Martin Schulz, Laura Carrington, Lingjia Tang, Jason Mars
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Journal environmental pollution
Year 2014
DOI
10.3233/SPR-140387
URL
http://dx.doi.org/10.3233/SPR-140387
Keywords
computer software

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