TY - GEN
T1 - Beyond the CPU
T2 - 28th International Supercomputing Conference on Supercomputing, ISC 2013
AU - McCraw, Heike
AU - Terpstra, Dan
AU - Dongarra, Jack
AU - Davis, Kris
AU - Musselman, Roy
PY - 2013
Y1 - 2013
N2 - The Blue Gene/Q (BG/Q) system is the third generation in the IBM Blue Gene line of massively parallel, energy efficient supercomputers that increases not only in size but also in complexity compared to its Blue Gene predecessors. Consequently, gaining insight into the intricate ways in which software and hardware are interacting requires richer and more capable performance analysis methods in order to be able to improve efficiency and scalability of applications that utilize this advanced system. The BG/Q predecessor, Blue Gene/P, suffered from incompletely implemented hardware performance monitoring tools. To address these limitations, an industry/academic collaboration was established early in BG/Q's development cycle to insure the delivery of effective performance tools at the machine's introduction. An extensive effort has been made to extend the Performance API (PAPI) to support hardware performance monitoring for the BG/Q platform. This paper provides detailed information about five recently added PAPI components that allow hardware performance counter monitoring of the 5D-Torus network, the I/O system and the Compute Node Kernel in addition to the processing cores on BG/Q. Furthermore, we explore the impact of node mappings on the performance of a parallel 3D-FFT kernel and use the new PAPI network component to collect hardware performance counter data on the 5D-Torus network. As a result, the network counters detected a large amount of redundant inter-node communications, which we were able to completely eliminate with the use of a customized node mapping.
AB - The Blue Gene/Q (BG/Q) system is the third generation in the IBM Blue Gene line of massively parallel, energy efficient supercomputers that increases not only in size but also in complexity compared to its Blue Gene predecessors. Consequently, gaining insight into the intricate ways in which software and hardware are interacting requires richer and more capable performance analysis methods in order to be able to improve efficiency and scalability of applications that utilize this advanced system. The BG/Q predecessor, Blue Gene/P, suffered from incompletely implemented hardware performance monitoring tools. To address these limitations, an industry/academic collaboration was established early in BG/Q's development cycle to insure the delivery of effective performance tools at the machine's introduction. An extensive effort has been made to extend the Performance API (PAPI) to support hardware performance monitoring for the BG/Q platform. This paper provides detailed information about five recently added PAPI components that allow hardware performance counter monitoring of the 5D-Torus network, the I/O system and the Compute Node Kernel in addition to the processing cores on BG/Q. Furthermore, we explore the impact of node mappings on the performance of a parallel 3D-FFT kernel and use the new PAPI network component to collect hardware performance counter data on the 5D-Torus network. As a result, the network counters detected a large amount of redundant inter-node communications, which we were able to completely eliminate with the use of a customized node mapping.
UR - http://www.scopus.com/inward/record.url?scp=84884470489&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-38750-0_16
DO - 10.1007/978-3-642-38750-0_16
M3 - Conference contribution
AN - SCOPUS:84884470489
SN - 9783642387494
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 213
EP - 225
BT - Supercomputing - 28th International Supercomputing Conference, ISC 2013, Proceedings
Y2 - 16 June 2013 through 20 June 2013
ER -
