Degree-of-Node Task Scheduling of Fine-Grained Parallel Programs on Heterogeneous Systems

• Published in: Journal of computer science and technology Vol. 34; no. 5; p. 1096
• Main Authors: Lin, Han, Li, Ming-Fan, Jia, Cheng-Fan, Liu, Jun-Nan, An, Hong
• Format: Journal Article
• Language: English
• Published: Springer 01.09.2019
• Subjects: Algorithms
• ISSN: 1000-9000
• DOI: 10.1007/s11390-0191962-4

Processor specialization has become the development trend of modern processor industry. It is quite possible that this will still be the main-stream in the next decades of semiconductor era. As the diversity of heterogeneous systems grows, organizing computation efficiently on systems with multiple kinds of heterogeneous processors is a challenging problem and will be a normality. In this paper, we analyze some state-of-the-art task scheduling algorithms of heterogeneous computing systems and propose a Degree of Node First (DONF) algorithm for task scheduling of fine-grained parallel programs on heterogeneous systems. The major innovations of DONF include: 1) simplifying task priority calculation for directed acyclic graph (DAG) based fine-grained parallel programs which not only reduces the complexity of task selection but also enables the algorithm to solve the scheduling problem for dynamic DAGs; 2) building a novel communication model in the processor selection phase that makes the task scheduling much more efficient. They are achieved by exploring fine-grained parallelism via a dataflow program execution model, and validated through experimental results with a selected set of benchmarks. The results on synthesized and real-world application DAGs show a very good performance. The proposed DONF algorithm significantly outperforms all the evaluated state-of-the-art heuristic algorithms in terms of scheduling length ratio (SLR) and efficiency. Keywords task scheduling, heterogeneous system, performance, parallel program