Power-Capped DVFS and Thread Allocation with ANN Models on Modern NUMA Systems

Satoshi Imamura, Hiroshi Sasaki, Koji Inoue, Dimitrios Nikolopoulos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)
402 Downloads (Pure)

Abstract

Abstract—Power capping is an essential function for efficient power budgeting and cost management on modern server systems. Contemporary server processors operate under power caps by using dynamic voltage and frequency scaling (DVFS). However, these processors are often deployed in non-uniform memory
access (NUMA) architectures, where thread allocation between cores may significantly affect performance and power consumption. This paper proposes a method which maximizes performance under power caps on NUMA systems by dynamically optimizing two knobs: DVFS and thread allocation. The method selects the optimal combination of the two knobs with models based on artificial neural network (ANN) that captures the nonlinear effect of thread allocation on performance. We implement
the proposed method as a runtime system and evaluate it with twelve multithreaded benchmarks on a real AMD Opteron based NUMA system. The evaluation results show that our method outperforms a naive technique optimizing only DVFS by up to
67.1%, under a power cap.
Original languageEnglish
Title of host publicationProceedings of the 32nd IEEE International Conference on Computer Design (ICCD).
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages324-331
ISBN (Electronic)978-1-4799-6492-5
DOIs
Publication statusPublished - 21 Oct 2014
EventThe 32nd IEEE International Conference on Computer Design - Novotel Ambassador Gangnam Hotel, Seoul, Korea, Republic of
Duration: 19 Oct 201422 Oct 2014

Conference

ConferenceThe 32nd IEEE International Conference on Computer Design
CountryKorea, Republic of
CitySeoul
Period19/10/201422/10/2014

Fingerprint Dive into the research topics of 'Power-Capped DVFS and Thread Allocation with ANN Models on Modern NUMA Systems'. Together they form a unique fingerprint.

Cite this