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FPL
2008
Springer

Mapping and scheduling with task clustering for heterogeneous computing systems

9 years 12 months ago
Mapping and scheduling with task clustering for heterogeneous computing systems
This paper presents a new approach for mapping task graphs to heterogeneous hardware/software computing systems using heuristic search techniques. Two techniques: (1) integration of clustering, mapping, and scheduling in a single step and (2) multiple neighborhood functions strategy are proposed to enhance quality of mapping/scheduling solutions. Our approach is demonstrated by case studies involving 40 randomly generated task graphs, as well as four real applications including signal processing and pattern recognition. Experimental results show that the proposed integrated approach outperforms a separate approach in terms of quality of the mapping/scheduling solution by up to 18.3% for a heterogeneous system which includes a microprocessor, a floating-point digital signal processor, and an FPGA.
Yuet Ming Lam, José Gabriel F. Coutinho, Wa
Added 26 Oct 2010
Updated 26 Oct 2010
Type Conference
Year 2008
Where FPL
Authors Yuet Ming Lam, José Gabriel F. Coutinho, Wayne Luk, Philip Heng Wai Leong
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