Academic Journals Database
Disseminating quality controlled scientific knowledge

Integrated Task Clustering, Mapping and Scheduling for Heterogeneous Computing Systems

Author(s): Yuet Ming Lam

Journal: International Journal of Computer Science & Information Technology
ISSN 0975-4660

Volume: 4;
Issue: 1;
Start page: 127;
Date: 2012;
VIEW PDF   PDF DOWNLOAD PDF   Download PDF Original page

Keywords: Hardware/software codesign | heuristic search | multiple neighborhood functions

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.
Affiliate Program     

Tango Jona
Tangokurs Rapperswil-Jona