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

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...

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Vydáno v:Journal of computer science and technology Ročník 34; číslo 5; s. 1096 - 1108
Hlavní autoři: Lin, Han, Li, Ming-Fan, Jia, Cheng-Fan, Liu, Jun-Nan, An, Hong
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.09.2019
Springer Nature B.V
School of Computer Science and Technology, University of Science and Technology of China, Hefei 230026, China
Témata:
Algorithms
Artificial Intelligence
Computer Science
Data Structures and Information Theory
Heuristic methods
Information Systems Applications (incl.Internet)
Microprocessors
Parallel programming
Regular Paper
Scheduling
Software Engineering
State-of-the-art reviews
Task scheduling
Theory of Computation
performance
task scheduling
parallel program
heterogeneous system
ISSN:1000-9000, 1860-4749
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Shrnutí: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 finegrained 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.
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ISSN:1000-9000
1860-4749
DOI:10.1007/s11390-019-1962-4