Title :
Modeling and Predicting Disk I/O Time of HPC Applications
Author :
Meswani, Mitesh R. ; Laurenzano, Michael A. ; Carrington, Laura ; Snavely, A.
Author_Institution :
San Diego Supercomput. Center, Univ. of California, San Diego, CA, USA
Abstract :
Understanding input/output (I/O) performance in high performance computing (HPC) is becoming increasingly important as the gap between the performance of computation and I/O widens. In this paper we propose a methodology to predict an application´s disk I/O time while running on High Performance Computing Modernization Program (HPCMP) systems. Our methodology consists of the following steps: 1) Characterize the I/O operations of an application running on a reference system. 2) Using a configurable I/O benchmark, collect statistics on the reference and target systems about the I/O operations that are relevant to the application on the reference and target systems. 3) Calculate a ratio between the measured I/O performance of the application on the reference system, with respect to target systems to predict the application´s I/O time on the target systems. Our results show that this methodology can accurately predict the I/O time of relevant HPC applications on HPCMP systems that have reasonably stable I/O performance run to run while systems that have wide variability in I/O performance are more difficult to predict accurately.
Keywords :
mainframes; performance evaluation; HPC application; HPCMP systems; configurable I/O benchmark; high performance computing modernization program system; input/output performance; stable I/O performance; Accuracy; Benchmark testing; Computational modeling; File systems; Instruments; Mathematical model; Predictive models; Benchmarking; HPC; I/O; Modeling; Performance; Prediction;
Conference_Titel :
High Performance Computing Modernization Program Users Group Conference (HPCMP-UGC), 2010 DoD
Conference_Location :
Schaumburg, IL
Print_ISBN :
978-1-61284-986-7
DOI :
10.1109/HPCMP-UGC.2010.27