GAP - A GENETIC ALGORITHM APPROACH TO OPTIMIZE 2-BIT DECODER PLAS
PLAs with two bit decoders at the inputs require a smaller area compared with standard two level PLAs. The number of product rows required for such PLas is a function of the assignment of pairs of variables to the decoders. This paper describes a minimization procedure that uses a genetic algorithm...
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| Other Authors: | , |
| Format: | article |
| Published: |
2020
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| Online Access: | https://eprints.kfupm.edu.sa/id/eprint/388/1/GAP_decoder.pdf |
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| Summary: | PLAs with two bit decoders at the inputs require a smaller area compared with standard two level PLAs. The number of product rows required for such PLas is a function of the assignment of pairs of variables to the decoders. This paper describes a minimization procedure that uses a genetic algorithm approach to reduce the size to the two bit decoder PLAs. Results are compared with those obtained by other approaches such as the Tomczuk and MIller heuristic and the simulated annealing technique (Abd-el-Barr and Choy 1993). For large randomly generated test cases and benchmarks, our results are optimal or very near optimal. |
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