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GRID
2008
Springer
15 years 6 months ago
Troubleshooting thousands of jobs on production grids using data mining techniques
Large scale production computing grids introduce new challenges in debugging and troubleshooting. A user that submits a workload consisting of tens of thousands of jobs to a grid ...
David A. Cieslak, Nitesh V. Chawla, Douglas Thain
162
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HPDC
2008
IEEE
15 years 5 months ago
A two-level scheduler to dynamically schedule a stream of batch jobs in large-scale grids
This paper describes the study conducted to design and evaluate a two-level on-line scheduler to dynamically schedule a stream of sequential and multi-threaded batch jobs on large...
Marco Pasquali, Ranieri Baraglia, Gabriele Capanni...
ADHOC
2008
122views more  ADHOC 2008»
15 years 5 months ago
Balancing computation and communication costs: The case for hybrid execution in sensor networks
Virtual machines (VM) are promising as system software in sensor networks. A major impediment to their widespread acceptance is their performance overhead. Compiling VM bytecode to...
Joel Koshy, Ingwar Wirjawan, Raju Pandey, Yann Ram...
FGCS
2002
89views more  FGCS 2002»
15 years 4 months ago
The Legion support for advanced parameter-space studies on a grid
Parameter-space studies involve running a single application several times with different parameter sets. Since the jobs are mutually independent, many computing resources can be r...
Anand Natrajan, Marty A. Humphrey, Andrew S. Grims...
IEEECIT
2010
IEEE
15 years 3 months ago
Scaling the iHMM: Parallelization versus Hadoop
—This paper compares parallel and distributed implementations of an iterative, Gibbs sampling, machine learning algorithm. Distributed implementations run under Hadoop on facilit...
Sebastien Bratieres, Jurgen Van Gael, Andreas Vlac...