TY - GEN
T1 - A Dynamic Programming Technique for Energy-Efficient Multicore Systems
AU - Hajiamini, Shervin
AU - Shirazi, Behrooz
AU - Crandall, Aaron
AU - Ghasemzadeh, Hassan
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/10
Y1 - 2018/10
N2 - With a focus on static (compile-time) methods for V/F level assignments, we propose an efficient Dynamic programming (DP) technique using the Viterbi algorithm, which uses the Energy-Delay Product (EDP) as objective function to predict the best V/F levels. By using the profiled information of applications, this technique minimizes energy consumption and execution time. We evaluate and compare the performance of the proposed algorithm against three heuristic methods-a greedy version of our algorithm, a feedback controller method, and a simple heuristic that uses historical performance to make predictions for adjusting the V/F levels. Experimental results show that our algorithm outperforms the heuristics under the study by an average of 12 to 24% using the EDP performance criteria.
AB - With a focus on static (compile-time) methods for V/F level assignments, we propose an efficient Dynamic programming (DP) technique using the Viterbi algorithm, which uses the Energy-Delay Product (EDP) as objective function to predict the best V/F levels. By using the profiled information of applications, this technique minimizes energy consumption and execution time. We evaluate and compare the performance of the proposed algorithm against three heuristic methods-a greedy version of our algorithm, a feedback controller method, and a simple heuristic that uses historical performance to make predictions for adjusting the V/F levels. Experimental results show that our algorithm outperforms the heuristics under the study by an average of 12 to 24% using the EDP performance criteria.
KW - Dynamic Programming
KW - Dynamic Voltage and Frequency Scaling
KW - Energy Efficiency
KW - The Viterbi Algorithm
UR - http://www.scopus.com/inward/record.url?scp=85069452129&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85069452129&partnerID=8YFLogxK
U2 - 10.1109/IGCC.2018.8752159
DO - 10.1109/IGCC.2018.8752159
M3 - Conference contribution
AN - SCOPUS:85069452129
T3 - 2018 9th International Green and Sustainable Computing Conference, IGSC 2018
BT - 2018 9th International Green and Sustainable Computing Conference, IGSC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th International Green and Sustainable Computing Conference, IGSC 2018
Y2 - 22 October 2018 through 24 October 2018
ER -