Self-Scheduling for a Heterogeneous Distributed Platform
By:
Luis A. García-González, César García-Jacas, Liesner
Acevedo-Martínez, Rafael A. Trujillo-Rasúa, and Dirk Roose
ABSTRACT
We discuss schedulers for a heterogeneous distributed platform, designed to execute a variety of tasks in a non-dedicated environment. The platform uses and controls a large number of non-dedicated heterogeneous computational resources in a local network. Several self-scheduling algorithms have been adapted to take into account the computational capacity of each workstation of the network. To evaluate the schedulers we use the platform to execute a software tool for molecular docking. We analyze the performance of the self-scheduling algorithms and their impact on the execution time of the application.
Key words: Heterogeneous distributed system, Task scheduling, Self-scheduling, Resilient distributed computing
References:
Garcıa-González, L.A., Garcıa-Jacas, C.R., Acevedo-Martınez, L., Trujillo-Rasúa, R.A. and Roose, D., 2017. Self-scheduling for a heterogeneous distributed platform. In Proceedings of the International Conference on Parallel Computing (pp. 232-241).
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