TY - GEN
T1 - Local discovery of system architecture - Application parameter sensitivity
T2 - 11th IEEE International Symposium on High Performance Distributed Computing, HPDC 2002
AU - Corey, I. R.
AU - Johnson, J. R.
AU - Vetter, J. S.
N1 - Publisher Copyright:
© 2002 IEEE.
PY - 2002
Y1 - 2002
N2 - This study presents a technique that can significantly improve the performance of a distributed application by allowing the application to locally adapt to architectural characteristics of distinct resources in a distributed system. Application performance is sensitive to system architecture-application parameter pairings. In a distributed or Grid enabled application, a single parameter configuration for the whole application will not always be optimal for every participating resource. In particular, some configurations can significantly degrade performance. Furthermore, the behavior of a system may change during the course of the run. The technique described here provides an automated mechanism for run-time adaptation of application parameters to the local system architecture. Using a scaled-down simulation of a Monte Carlo physics code, we demonstrate that this technique can conservatively achieve speedups up to 65% on individual resources and may even provide order of magnitude speedup in the extreme case.
AB - This study presents a technique that can significantly improve the performance of a distributed application by allowing the application to locally adapt to architectural characteristics of distinct resources in a distributed system. Application performance is sensitive to system architecture-application parameter pairings. In a distributed or Grid enabled application, a single parameter configuration for the whole application will not always be optimal for every participating resource. In particular, some configurations can significantly degrade performance. Furthermore, the behavior of a system may change during the course of the run. The technique described here provides an automated mechanism for run-time adaptation of application parameters to the local system architecture. Using a scaled-down simulation of a Monte Carlo physics code, we demonstrate that this technique can conservatively achieve speedups up to 65% on individual resources and may even provide order of magnitude speedup in the extreme case.
KW - Application software
KW - Computer applications
KW - Computer architecture
KW - Degradation
KW - Distributed computing
KW - Laboratories
KW - Monte Carlo methods
KW - Performance evaluation
KW - Processor scheduling
KW - Runtime
UR - http://www.scopus.com/inward/record.url?scp=84949218143&partnerID=8YFLogxK
U2 - 10.1109/HPDC.2002.1029940
DO - 10.1109/HPDC.2002.1029940
M3 - Conference contribution
AN - SCOPUS:84949218143
T3 - Proceedings of the IEEE International Symposium on High Performance Distributed Computing
SP - 399
EP - 407
BT - Proceedings - 11th IEEE International Symposium on High Performance Distributed Computing, HPDC 2002
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 24 July 2002 through 26 July 2002
ER -