Parallel processing (Electronic computers), Electronic data processing -- Distributed processing, Computer network architectures, System analysis -- Data processing
In using a shared network of workstations for parallel processing, it is not only important to consider heterogeneity and differences in processing power between the workstations but also the dynamics of the system as a whole. In such a computing environment where the use of resources vary as other applications consume and release resources, intelligent scheduling of the parallel jobs onto the available resources is essential to maximize resource utilization. Despite this realization, however, there are few systems available that provide an infrastructure for the easy development and testing of these intelligent schedulers. In this paper, an infrastructure is presented together with a scheduler that is capable of both gang scheduling and dynamic task reallocation of PVM applications.
"Scheduling of Parallel Jobs on Dynamic, Heterogenous Networks," Dan L. Clark, Jeremy Casas, Steve W. Otto, Robert M. Prouty, Jonathan Walpole Technical report, Dept. of Comp. Sci., Oregon Graduate Institute of Science and Technology, January, 1995.
A Technical Report produced by the Oregon Graduate Institute of Science and Technology Department of Computer Science.