TY - GEN
T1 - I/O Aware Power Shifting
AU - Savoie, Lee
AU - Lowenthal, David K.
AU - Supinski, Bronis R.De
AU - Islam, Tanzima
AU - Mohror, Kathryn
AU - Rountree, Barry
AU - Schulz, Martin
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/7/18
Y1 - 2016/7/18
N2 - Power limits on future high-performance computing (HPC) systems will constrain applications. However, HPC applications do not consume constant power over their lifetimes. Thus, applications assigned a fixed power bound may be forced to slow down during high-power computation phases, but may not consume their full power allocation during low-power I/O phases. This paper explores algorithms that leverage application semantics - phase frequency, duration and power needs - to shift unused power from applications in I/O phases to applications in computation phases, thus improving system-wide performance. We design novel techniques that include explicit staggering of applications to improve power shifting. Compared to executing without power shifting, our algorithms can improve average performance by up to 8% or improve performance of a single, high-priority application by up to 32%.
AB - Power limits on future high-performance computing (HPC) systems will constrain applications. However, HPC applications do not consume constant power over their lifetimes. Thus, applications assigned a fixed power bound may be forced to slow down during high-power computation phases, but may not consume their full power allocation during low-power I/O phases. This paper explores algorithms that leverage application semantics - phase frequency, duration and power needs - to shift unused power from applications in I/O phases to applications in computation phases, thus improving system-wide performance. We design novel techniques that include explicit staggering of applications to improve power shifting. Compared to executing without power shifting, our algorithms can improve average performance by up to 8% or improve performance of a single, high-priority application by up to 32%.
KW - HPC
KW - Performance
KW - Power
UR - http://www.scopus.com/inward/record.url?scp=84983283657&partnerID=8YFLogxK
U2 - 10.1109/IPDPS.2016.15
DO - 10.1109/IPDPS.2016.15
M3 - Conference contribution
AN - SCOPUS:84983283657
T3 - Proceedings - 2016 IEEE 30th International Parallel and Distributed Processing Symposium, IPDPS 2016
SP - 740
EP - 749
BT - Proceedings - 2016 IEEE 30th International Parallel and Distributed Processing Symposium, IPDPS 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 30th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2016
Y2 - 23 May 2016 through 27 May 2016
ER -