Integrated Task Clustering, Mapping and Scheduling for Heterogeneous Computing Systems
Yuet Ming Lam · International Journal of Computer Science and Information Technology · 2012
This paper presents a new approach for mapping and scheduling task graphs for heterogeneous hardware/software computing systems using heuristic search.Task mapping and scheduling are vital in hardware/software codesign and previous approaches that treat them separately lead to suboptimal solutions.In this paper, we propose two techniques to enhance the speedup of mapping/scheduling solutions: (1) an integrated technique combining task clustering, mapping, and scheduling, and (2) a multiple neighborhood function strategy.Our approach is demonstrated by case studies involving 40 randomly generated task graphs, as well as six applications.Experimental results show that our proposed approach outperforms a separate approach in terms of speedup by up to 18.3% for a system with a microprocessor, a floating-point digital signal processor, and an FPGA.