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» Regret Minimization and Job Scheduling
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CCGRID
2008
IEEE
14 years 2 months ago
Grid Differentiated Services: A Reinforcement Learning Approach
—Large scale production grids are a major case for autonomic computing. Following the classical definition of Kephart, an autonomic computing system should optimize its own beha...
Julien Perez, Cécile Germain-Renaud, Bal&aa...
CLUSTER
2004
IEEE
13 years 11 months ago
A comparison of local and gang scheduling on a Beowulf cluster
Gang Scheduling and related techniques are widely believed to be necessary for efficientjob scheduling on distributed memory parallel computers. This is hecause they minimize cont...
Peter E. Strazdins, John Uhlmann
ECCC
2000
140views more  ECCC 2000»
13 years 7 months ago
Randomized Approximation Schemes for Scheduling Unrelated Parallel Machines
We consider the problem of Scheduling n Independent Jobs on m Unrelated Parallel Machines, when the number of machines m is xed. We address the standard problem of minimizing the ...
Pavlos Efraimidis, Paul G. Spirakis
ICS
2005
Tsinghua U.
14 years 1 months ago
Power-aware resource allocation in high-end systems via online simulation
Traditionally, scheduling in high-end parallel systems focuses on how to minimize the average job waiting time and on how to maximize the overall system utilization. Despite the d...
Barry Lawson, Evgenia Smirni
CEE
2007
107views more  CEE 2007»
13 years 7 months ago
A non-preemptive scheduling algorithm for soft real-time systems
Real-time systems are often designed using preemptive scheduling and worst-case execution time estimates to guarantee the execution of high priority tasks. There is, however, an i...
Wenming Li, Krishna M. Kavi, Robert Akl