Tabu search based cells placement in nanofabric architectures with restricted connectivity

S. M. Sait, A. Arafeh
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引用次数: 2

Abstract

New advances in nano-electronics have led to the introduction of CMOL (CMOS/Nano-devices hybrid) circuits which consists of an overlay of a nanowires over a CMOS stack. CMOL circuits can implement a netlist of NOR gates and Inverters using diode-like nanodevices. CMOL has inherently restricted connectivity due to limited nanowires length. Therefore connectivity of the circuit's elements is constrained to be within a certain radius, else an intermediary buffers are required. In this paper we present a Tabu search (TS) algorithm to address cells placement problem in CMOL. The Heuristic is engineered to provide feasible circuit implementations by efficient exploration of search space. Empirical results for ISCAS'89 benchmarks are compared with previous solutions using GA, MA, and LRMA heuristics. Results show that in almost all cases, TS exhibits more intelligent search of the solutions subspace, and is able to find better solutions. For all tested benchmarks over 90% reduction in average CPU processing time when compared with best published techniques was obtained.
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连接受限的纳米结构中基于禁忌搜索的细胞放置
纳米电子学的新进展导致了CMOL (CMOS/纳米器件混合)电路的引入,该电路由纳米线覆盖在CMOS堆栈上组成。CMOL电路可以使用类似二极管的纳米器件实现NOR门和逆变器的网络列表。由于纳米线的长度有限,CMOL的连接性受到限制。因此,电路元件的连通性被限制在一定的半径内,否则需要中间缓冲区。本文提出了一种禁忌搜索(TS)算法来解决CMOL中细胞的放置问题。启发式设计通过对搜索空间的有效探索来提供可行的电路实现。ISCAS'89基准的实证结果与以前使用GA, MA和LRMA启发式的解决方案进行了比较。结果表明,在几乎所有情况下,TS都表现出更智能的解子空间搜索,能够找到更好的解。对于所有测试基准,与已发表的最佳技术相比,平均CPU处理时间减少了90%以上。
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