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A Low Overhead Quasi-Delay-Insensitive (QDI) Asynchronous Data Path Synthesis Based on Microcell-Interleaving Genetic Algorithm (MIGA)

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4 Author(s)
Rong Zhou ; Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore ; Kwen-Siong Chong ; Bah-Hwee Gwee ; Joseph S. Chang

In this paper, we propose a design approach to mitigate the hardware overhead of the data completion detection circuit in quasi-delay-insensitive (QDI) asynchronous-logic circuits. In this proposed design approach, three novelties are highlighted. Firstly, a novel microcell-interleaving approach is proposed to reduce the number of completion detection (CD) circuits while retaining the required QDI attribute. Secondly, we analyze the performance of the QDI circuits based on the proposed microcell-interleaving approach graphically in terms of power dissipation, transistor count and delay, and evaluate/determine the upper and lower boundaries of these performance profiles. Thirdly, we propose a microcell-interleaving genetic algorithm (MIGA) to stochastically optimize the proposed microcell-interleaving approach on power dissipation, transistor count, and delay. To validate the proposed design approach, a complete performance profile of ISCAS-85 C499 circuit is investigated on the basis of differential cascode voltage switch logic (DCVSL) and dynamic strong indicating (DSI) microcells. We demonstrate the efficiency of the proposed design approach by benchmarking against the competing DCVSL, null convention logic and DSI designs on five ISCAS-85 circuits. Specifically, the proposed designs, on average, are 1.77 × better in power dissipation, 1.4 × better in area, and 1.58 × better in a composite metric of power × area × delay, and reasonably slower for the lowest power dissipation points. We further demonstrate the practicality of the proposed design approach by implementing an 8-tap 16-bit asynchronous QDI finite impulse response filter. Finally, we demonstrate the ~10% and ~11% improved efficiency of the proposed MIGA over the greedy algorithm and dynamic programming, respectively.

Published in:

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems  (Volume:33 ,  Issue: 7 )