Adaptive Scheduling for Task Farming with Grid Middleware
James S. Plank,
The International Journal of High
Volume 13, Number 3, Fall, 1999. pp. 231 - 240. Sage Science Press.
Scheduling in metacomputing environments is an active field of research
as the vision of a Computational Grid becomes more concrete.
An important class of Grid applications are
long-running parallel computations with large numbers of
somewhat independent tasks (Monte Carlo simulations, parameter-space
searches, etc.). A number of Grid middleware projects are available
to implement such applications, but scheduling strategies are still
open research issues. This is mainly due to the diversity of both
Grid resource types and their availability patterns. The
purpose of this work is to develop and validate a general
adaptive scheduling algorithm for task farming applications
along with a user interface that makes the algorithm
accessible to domain scientists. The authors' algorithm
is general in that it is not tailored to a particular Grid middleware
and it requires very few assumptions concerning the nature of the resources.
Their first testbed is NetSolve as it asllows quick and easy development
of the algorithm by isolating the developer from issues such as
process control, I/O, remote software access, or fault-tolerance.
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- Plain Text:
author H. Casanova and M. Kim and J. S. Plank and J. Dongarra
title Adaptive Scheduling for Task Farming with Grid Middleware
journal International Journal of High Performance Computing
publisher Sage Science Press
author = "H. Casanova and M. Kim and J. S. Plank and J. Dongarra",
title = "Adaptive Scheduling for Task Farming with Grid Middleware",
journal = "International Journal of High Performance Computing",
volume = "13",
number = "3",
month = "Fall",
year = "1999",
pages = "231-240",
publisher = "Sage Science Press"