%0 Journal Article
%T Integrated Task Clustering, Mapping and Scheduling for Heterogeneous Computing Systems
%A Yuet Ming Lam
%J International Journal of Computer Science & Information Technology
%D 2012
%I Academy & Industry Research Collaboration Center (AIRCC)
%X 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.
%K Hardware/software codesign
%K heuristic search
%K multiple neighborhood functions
%U http://airccse.org/journal/jcsit/0212csit11.pdf