TY - GEN
T1 - Combining phase identification and statistic modeling for automated parallel benchmark generation
AU - Jin, Ye
AU - Liu, Mingliang
AU - Ma, Xiaosong
AU - Liu, Qing
AU - Logan, Jeremy
AU - Podhorszki, Norbert
AU - Choi, Jong Youl
AU - Klasky, Scott
PY - 2015/1/24
Y1 - 2015/1/24
N2 - Parallel application benchmarks are indispensable for evaluating/optimizing HPC software and hardware. However, it is very challenging and costly to obtain high-fidelity benchmarks reflecting the scale and complexity of state-of-the-art parallel applications. Hand-extracted synthetic benchmarks are time- and labor-intensive to create. Real applications themselves, while offering most accurate performance evaluation, are expensive to compile, port, reconfigure, and often plainly inaccessible due to security or ownership concerns. This work contributes APPRIME, a novel tool for trace-based automatic parallel benchmark generation. Taking as input standard communication-I/O traces of an application's execution, it couples accurate automatic phase identification with statistical regeneration of event parameters to create compact, portable, and to some degree reconfigurable parallel application benchmarks. Experiments with four NAS Parallel Benchmarks (NPB) and three real scientific simulation codes confirm the fidelity of APPRIME benchmarks. They retain the original applications' performance characteristics, in particular the relative performance across platforms.
AB - Parallel application benchmarks are indispensable for evaluating/optimizing HPC software and hardware. However, it is very challenging and costly to obtain high-fidelity benchmarks reflecting the scale and complexity of state-of-the-art parallel applications. Hand-extracted synthetic benchmarks are time- and labor-intensive to create. Real applications themselves, while offering most accurate performance evaluation, are expensive to compile, port, reconfigure, and often plainly inaccessible due to security or ownership concerns. This work contributes APPRIME, a novel tool for trace-based automatic parallel benchmark generation. Taking as input standard communication-I/O traces of an application's execution, it couples accurate automatic phase identification with statistical regeneration of event parameters to create compact, portable, and to some degree reconfigurable parallel application benchmarks. Experiments with four NAS Parallel Benchmarks (NPB) and three real scientific simulation codes confirm the fidelity of APPRIME benchmarks. They retain the original applications' performance characteristics, in particular the relative performance across platforms.
KW - Automatic benchmark generation
KW - HPC applications
KW - Phase identification
KW - Statistical profiling
KW - Trace
UR - http://www.scopus.com/inward/record.url?scp=84939146769&partnerID=8YFLogxK
U2 - 10.1145/2688500.2688541
DO - 10.1145/2688500.2688541
M3 - Conference contribution
AN - SCOPUS:84939146769
T3 - Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP
SP - 269
EP - 270
BT - 20th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2015 - Proceedings
PB - Association for Computing Machinery
T2 - 20th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2015
Y2 - 7 February 2015 through 11 February 2015
ER -