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HPDC
2002
IEEE
15 years 6 months ago
Decoupling Computation and Data Scheduling in Distributed Data-Intensive Applications
In high energy physics, bioinformatics, and other disciplines, we encounter applications involving numerous, loosely coupled jobs that both access and generate large data sets. So...
Kavitha Ranganathan, Ian T. Foster
PDP
2010
IEEE
15 years 5 months ago
Malleable-Lab: A Tool for Evaluating Adaptive Online Schedulers on Malleable Jobs
—The emergence of multi-core computers has led to explosive development of parallel applications and hence the need of efficient schedulers for parallel jobs. Adaptive online sc...
Yangjie Cao, Hongyang Sun, Wen-Jing Hsu, Depei Qia...
CCGRID
2005
IEEE
15 years 7 months ago
Experiences with the KOALA co-allocating scheduler in multiclusters
In multicluster systems, and more generally, in grids, jobs may require co-allocation, i.e., the simultaneous allocation of resources such as processors and input files in multip...
Hashim H. Mohamed, Dick H. J. Epema
ESA
2008
Springer
95views Algorithms» more  ESA 2008»
15 years 3 months ago
Speed Scaling Functions for Flow Time Scheduling Based on Active Job Count
Abstract. We study online scheduling to minimize flow time plus energy usage in the dynamic speed scaling model. We devise new speed scaling functions that depend on the number of ...
Tak Wah Lam, Lap-Kei Lee, Isaac Kar-Keung To, Prud...
ICDCS
2000
IEEE
15 years 6 months ago
Improving Distributed Workload Performance by Sharing both CPU and Memory Resources
We develop and examine job migration policies by considering effective usage of global memory in addition to CPU load sharing in distributed systems. When a node is identified fo...
Xiaodong Zhang, Yanxia Qu, Li Xiao