A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is
In the era of petascale supercomputing, the importance of load balancing is crucial. Although dynamic load balancing is widespread, it is increasingly difficult to implement effectively with thousands of processors or more, prompting a second look at static load-balancing techniques even though the optimal allocation of tasks to processors is an NP-hard problem. We propose a heuristic static load-balancing algorithm, employing fitted benchmarking data, as an alternative to dynamic loaddoi:10.1109/sc.2012.62 dblp:conf/sc/AlexeevMLFF12 fatcat:ed4cztal7nhp7ddqnti4ypsvuq