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Archit. Code Optim."],"published-print":{"date-parts":[[2012,9]]},"abstract":"<jats:p>This article proposes a runtime model that relates server energy consumption to its overall thermal envelope, using hardware performance counters and experimental measurements. While previous studies have attempted system-wide modeling of server power consumption through subsystem models, our approach is different in that it links system energy input to subsystem energy consumption based on a small set of tightly correlated parameters. The proposed model takes into account processor power, bus activities, and system ambient temperature for real-time prediction on the power consumption of long running jobs. Using the HyperTransport and QuickPath Link structures as case studies and through electrical measurements on example server subsystems, we develop a chaotic time-series approximation for runtime power consumption, arriving at the Chaotic Attractor Predictor (CAP). With polynomial time complexity, CAP exhibits high prediction accuracy, having the prediction errors within 1.6% (or 3.3%) for servers based on the HyperTransport bus (or the QuickPath Links), as verified by a set of common processor benchmarks. Our CAP is a superior predictive mechanism over existing linear auto-regressive methods, which require expensive and complex corrective steps to address the nonlinear and chaotic aspects of the underlying physical system.<\/jats:p>","DOI":"10.1145\/2355585.2355588","type":"journal-article","created":{"date-parts":[[2012,10,2]],"date-time":"2012-10-02T13:50:00Z","timestamp":1349185800000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":21,"title":["Runtime energy consumption estimation for server workloads based on chaotic time-series approximation"],"prefix":"10.1145","volume":"9","author":[{"given":"Adam Wade","family":"Lewis","sequence":"first","affiliation":[{"name":"University of Louisiana at Lafayette, Lafayette, LA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nian-Feng","family":"Tzeng","sequence":"additional","affiliation":[{"name":"University of Louisiana at Lafayette, Lafayette, LA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Soumik","family":"Ghosh","sequence":"additional","affiliation":[{"name":"University of Louisiana at Lafayette"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2012,10,5]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"AMD. 2006. 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