ABSTRACT
Efficient scheduling algorithms play an essential part in heterogeneous computing systems to achieve high performance. The problem of producing an optimal schedule for the precedence-constrained tasks is recognized to be an NP-complete problem. To work out this problem, the researchers have already been proposed various scheduling algorithms in the literature. This paper discusses four well-known list scheduling algorithms such as HEFT, Lookahead, CEFT and PEFT for heterogeneous computing systems and performs experiments for randomly created application graphs and the application graphs generated from real-world problem for instance molecular dynamic code. The performance of algorithms are evaluated and compared on different scheduling parameters such as scheduling length ratio, efficiency, etc.
- Hamid Arabnejad and Jorge G Barbosa. 2014. List scheduling algorithm for heterogeneous systems by an optimistic cost table. IEEE Transactions on Parallel and Distributed Systems 25, 3 (2014), 682--694. Google ScholarDigital Library
- Luiz F Bittencourt, Rizos Sakellariou, and Edmundo RM Madeira. 2010. Dag scheduling using a lookahead variant of the heterogeneous earliest finish time algorithm. In Parallel, Distributed and Network-Based Processing (PDP), 2010 18th Euromicro International Conference on. IEEE, 27--34.Google ScholarDigital Library
- Menglan Hu, Jun Luo, Yang Wang, and Bharadwaj Veeravalli. 2017. Adaptive Scheduling of Task Graphs with Dynamic Resilience. IEEE Trans. Comput. 66, 1 (2017), 17--23. Google ScholarDigital Library
- Hidehiro Kanemitsu, Masaki Hanada, and Hidenori Nakazato. 2016. Clustering-based task scheduling in a large number of heterogeneous processors. IEEE Transactions on Parallel and Distributed Systems 27, 11 (2016), 3144--3157. Google ScholarDigital Library
- Minhaj Ahmad Khan. 2012. Scheduling for heterogeneous systems using constrained critical paths. Parallel Comput. 38, 4 (2012), 175--193. Google ScholarDigital Library
- Yu-Kwong Kwok and Ishfaq Ahmad. 1996. Dynamic critical-path scheduling: An effective technique for allocating task graphs to multiprocessors. IEEE transactions on parallel and distributed systems 7, 5 (1996), 506--521. Google ScholarDigital Library
- Yu-Kwong Kwok and Ishfaq Ahmad. 1999. Static scheduling algorithms for allocating directed task graphs to multiprocessors. ACM Computing Surveys (CSUR) 31, 4 (1999), 406--471. Google ScholarDigital Library
- Christos H Papadimitriou and Mihalis Yannakakis. 1990. Towards an architecture-independent analysis of parallel algorithms. SIAM journal on computing 19, 2 (1990), 322--328. Google ScholarDigital Library
- Vivek Sarkar. 1987. Partitioning and scheduling parallel programs for execution on multiprocessors. Technical Report. Stanford Univ., CA (USA). Google ScholarCross Ref
- Zhiao Shi, Emmanuel Jeannot, and Jack J Dongarra. 2006. Robust task scheduling in non-deterministic heterogeneous computing systems. In Cluster Computing, 2006 IEEE International Conference on. IEEE, 1--10.Google ScholarCross Ref
- Xiaoyong Tang, Kenli Li, Guiping Liao, and Renfa Li. 2010. List scheduling with duplication for heterogeneous computing systems. Journal of parallel and distributed computing 70, 4 (2010), 323--329. Google ScholarDigital Library
- Haluk Topcuoglu, Salim Hariri, and Min-you Wu. 2002. Performance-effective and low-complexity task scheduling for heterogeneous computing. IEEE transactions on parallel and distributed systems 13, 3 (2002), 260--274. Google ScholarDigital Library
- M-Y Wu and Daniel D Gajski. 1990. Hypertool: A programming aid for message-passing systems. IEEE transactions on parallel and distributed systems 1, 3 (1990), 330--343. Google ScholarDigital Library
- Tao Yang and Apostolos Gerasoulis. 1994. DSC: Scheduling parallel tasks on an unbounded number of processors. IEEE Transactions on Parallel and Distributed Systems 5, 9 (1994), 951--967. Google ScholarDigital Library
Index Terms
- Performance Comparison of HEFT, Lookahead, CEFT and PEFT Scheduling Algorithms for Heterogeneous Computing Systems
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