GridPac: A Resource Management System for Energy and Performance Optimization on Computational Grids (funded by the National Science Foundation)
Massive energy consumption is an escalating threat to the environment.
Large-scale computational grids consume substantial amount of energy, and
their energy requirements for powering and cooling are becoming comparable
to the costs of acquisition. There is a lack of generally applicable methods
for reducing energy consumption while ensuring good quality of service. This
project will develop GridPac (Grid with Power-Aware Computing), a middleware
environment that will allow grid managers and service providers to schedule
multiple workflows across a distributed grid for system-wide optimization.
GridPac will be based on a novel framework to support a variety of
task-level workflows. The main features of this work are to develop:
(a) Novel static and dynamic algorithms for scheduling single and multiple
workflows, which can be flexibly utilized by service providers in scalable
(b) Control algorithms to account for dynamic adjustment of schedules using
energy monitoring of the grid resources.
(c) Extensive benchmarking using a suite of commonly used grid workflows.
(d) A prototype middleware to assist IT organizations to better support
their users while reducing energy costs.
The proposed work will lead to original scholarly contributions while
harnessing the usage of computational grids. The project carries tremendous
potential for economic, environmental, and societal impact. We will initiate
new graduate and undergraduate level courses on related topics, and develop
relevant tutorials, which will help to create awareness and educate a large
audience on a critically important research topic.