A novel genetic algorithm for variable partition of dual memory bank DSPs

Authors:
Dan Zhang;Zeng-Zhi Li;Hai Wang;Tao Zhan
Affiliations:
School of Electronics & Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China;School of Electronics & Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China;School of Electronics & Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China;Dept. of Computer Science & Engineering, Northwest Polytechnical University, Xi'an, Shaanxi, China
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
Year:
2005

Citing 3
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Abstract

DSPs provide high performance and low cost through their use of specialized hardware features. One feature commonly found in DSPs is the dual data memory banks to offer high memory bandwidth. However, it poses problems for C compilers, which are mostly not capable of assigning variables between banks. In this paper, an immune genetic algorithm for variable partition between data banks is presented to maximize the benefit of this feature. In our approach, the reduced interference graph of variable accesses is constructed, the potential variable partitions are represented as antibodies and the vaccines are abstracted; then through some operations including adaptive vaccination, immune selection and so on, the antibodies can converge at optimal variable partitions. Experimental results show that our algorithm is superior to previous works in terms of performance and code size.