Performance Evaluation of Quine-McCluskey Method on Multi-core CPU
Hoang-Gia Vu, Ngoc-Dai Bui, Anh‐Tu Nguyen, ThanhBangLe · 2021 8th NAFOSTED Conference on Information and Computer Science (NICS) · 2021
The Quine-McCluskey method is an algorithm to minimize Boolean functions. Although the method can be programmed on computers, it takes a long time to return the set of prime implicants, thus slowing the analysis and design of digital logic circuits. As a result, it slows down the dynamic reconfiguration process of programmable logic devices. In this paper, we first propose a data representation for storing implicants in memory to reduce the cache misses of the program. We then propose an algorithm to find all prime implicants of a Boolean function. The algorithm aims to reuse the data available on cache, thus decreasing cache misses. After that, we propose an algorithm for step 2 of the Quine-McCluskey method to select the minimal number of essential prime implicants. The evaluation shows that our proposals achieve much higher performance than the original Quine-McCluskey method. The number of essential prime implicants is a low percentage, less than 50%, of the total prime implicants generated in step 1 of the method.