Kohonen神經(jīng)網(wǎng)絡(luò)在時(shí)延驅(qū)動(dòng)布局中的應(yīng)用
APPLICATION OF SELF-ORGANIZING NEURAL NETWORK IN TIMING-DRIVEN PLACEMENT
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摘要: 本文提出一個(gè)基于Kohonen自組織神經(jīng)網(wǎng)絡(luò)的以關(guān)鍵路徑時(shí)延最小為優(yōu)化目標(biāo)的時(shí)延驅(qū)動(dòng)布局算法。算法的關(guān)鍵是建立面向線網(wǎng)的樣本矢量。與面向單元的樣本矢量相比,面向線網(wǎng)的樣本矢量不僅可以直接處理多端線網(wǎng),而且能夠描述時(shí)延信息。實(shí)驗(yàn)結(jié)果表明,這是一種有效的方法。Abstract: In this paper, a timing-driven placement algorithm using Kohonen self-organizing is proposed. The object function of the algorithm is to minimize the critical nets. In the algorithm, net-based similarity vector is presented. Compared with the cell-based similarity vector, net-based similarity vector not only can directly deal with the multi-terminal nets, but also can describe the information about timing. The experimental result shows that it is a effective method.
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