TY - GEN
T1 - Just in time dynamic voltage scaling
T2 - 2005 ACM/IEEE Conference on Supercomputing, SC 2005
AU - Kappiah, Nandini
AU - Freeh, Vincent W.
AU - Lowenthal, David K.
N1 - Publisher Copyright:
© 2005 IEEE.
PY - 2005
Y1 - 2005
N2 - Recently, improving the energy efficiency of HPC machines has become important. As a result, interest in using power-scalable clusters, where frequency and voltage can be dynamically modified, has increased. On power-scalable clusters, one opportunity for saving energy with little or no loss of performance exists when the computational load is not perfectly balanced. This situation occurs frequently, as balancing load between nodes is one of the long standing problems in parallel and distributed computing. In this paper we present a system called Jitter, which reduces the frequency on nodes that are assigned less computation and therefore have slack time. This saves energy on these nodes, and the goal of Jitter is to attempt to ensure that they arrive “just in time” so that they avoid increasing overall execution time. For example, in Aztec, from the ASCI Purple suite, our algorithm uses 8% less energy while increasing execution time by only 2.6%.
AB - Recently, improving the energy efficiency of HPC machines has become important. As a result, interest in using power-scalable clusters, where frequency and voltage can be dynamically modified, has increased. On power-scalable clusters, one opportunity for saving energy with little or no loss of performance exists when the computational load is not perfectly balanced. This situation occurs frequently, as balancing load between nodes is one of the long standing problems in parallel and distributed computing. In this paper we present a system called Jitter, which reduces the frequency on nodes that are assigned less computation and therefore have slack time. This saves energy on these nodes, and the goal of Jitter is to attempt to ensure that they arrive “just in time” so that they avoid increasing overall execution time. For example, in Aztec, from the ASCI Purple suite, our algorithm uses 8% less energy while increasing execution time by only 2.6%.
UR - http://www.scopus.com/inward/record.url?scp=85117234815&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85117234815&partnerID=8YFLogxK
U2 - 10.1109/SC.2005.39
DO - 10.1109/SC.2005.39
M3 - Conference contribution
AN - SCOPUS:85117234815
T3 - Proceedings of the International Conference on Supercomputing
BT - Proceedings of the ACM/IEEE SC 2005 Conference, SC 2005
PB - Association for Computing Machinery
Y2 - 12 November 2005 through 18 November 2005
ER -