TY - GEN
T1 - Integrating Abstractions to Enhance the Execution of Distributed Applications
AU - Turilli, Matteo
AU - Liu, Feng
AU - Zhang, Zhao
AU - Merzky, Andre
AU - Wilde, Michael
AU - Weissman, Jon
AU - Katz, Daniel S.
AU - Jha, Shantenu
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/7/18
Y1 - 2016/7/18
N2 - One of the factors that limits the scale, performance, and sophistication of distributed applications is the difficulty of concurrently executing them on multiple distributed computing resources. In part, this is due to a poor understanding of the general properties and performance of the coupling between applications and dynamic resources. This paper addresses this issue by integrating abstractions representing distributed applications, resources, and execution processes into a pilot-based middleware. The middleware provides a platform that can specify distributed applications, execute them on multiple resource and for different configurations, and is instrumented to support investigative analysis. We analyzed the execution of distributed applications using experiments that measure the benefits of using multiple resources, the late-binding of scheduling decisions, and the use of backfill scheduling.
AB - One of the factors that limits the scale, performance, and sophistication of distributed applications is the difficulty of concurrently executing them on multiple distributed computing resources. In part, this is due to a poor understanding of the general properties and performance of the coupling between applications and dynamic resources. This paper addresses this issue by integrating abstractions representing distributed applications, resources, and execution processes into a pilot-based middleware. The middleware provides a platform that can specify distributed applications, execute them on multiple resource and for different configurations, and is instrumented to support investigative analysis. We analyzed the execution of distributed applications using experiments that measure the benefits of using multiple resources, the late-binding of scheduling decisions, and the use of backfill scheduling.
KW - Abstractions
KW - Distributed systems
KW - Execution strategies
KW - Middleware
UR - http://www.scopus.com/inward/record.url?scp=84983343673&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84983343673&partnerID=8YFLogxK
U2 - 10.1109/IPDPS.2016.64
DO - 10.1109/IPDPS.2016.64
M3 - Conference contribution
AN - SCOPUS:84983343673
T3 - Proceedings - 2016 IEEE 30th International Parallel and Distributed Processing Symposium, IPDPS 2016
SP - 953
EP - 962
BT - Proceedings - 2016 IEEE 30th International Parallel and Distributed Processing Symposium, IPDPS 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 30th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2016
Y2 - 23 May 2016 through 27 May 2016
ER -