An Experimental Assessment of Express Parallel Programming Environment
MASCOTS '95 Proceedings of the 3rd International Workshop on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems
HCW '99 Proceedings of the Eighth Heterogeneous Computing Workshop
Run-Time Statistical Estimation of Task Execution Times for Heterogeneous Distributed Computing
HPDC '96 Proceedings of the 5th IEEE International Symposium on High Performance Distributed Computing
Dynamic Mapping in Energy Constrained Heterogeneous Computing Systems
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
Dynamic resource allocation heuristics that manage tradeoff between makespan and robustness
The Journal of Supercomputing
Dynamic Grid Scheduling Using Job Runtime Requirements and Variable Resource Availability
Euro-Par '08 Proceedings of the 14th international Euro-Par conference on Parallel Processing
Trace-based evaluation of job runtime and queue wait time predictions in grids
Proceedings of the 18th ACM international symposium on High performance distributed computing
Autonomic metered pricing for a utility computing service
Future Generation Computer Systems
Scheduling in HC and Grids Using a Parallel CHC
Computational Intelligence
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For managing tasks efficiently in a Distributed Het erogeneous Supercomputing System (DHSS) , we re quire a thorough understanding of applications and their intelligent scheduling within the system. For this purpose, an accurate estimation of the execu tion time of applications on various architectures is needed. In this paper we present a framework to ad dress this issue. We propose two techniques, called augmented code profiling and augmented analytical benchmarking, to characterize applications and archi tectures in a DHSS, respectively. These techniques are based on code profiling and analytical benchmarking, respectively and provide a detailed architectural-dependent characterization of DHSS applications.