An evolution-based technique for local microcode compaction

I. Ahmad, M. Dhodhi, K. Saleh
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引用次数: 4

Abstract

In this paper we present a variant of the simulated evolution technique for local microcode compaction. The simulated evolution is a general optimization method based on an analogy with the natural selection process in biological evolution. The proposed technique combines simulated evolution with list scheduling, in which simulated evolution is used to determine suitable priorities which lead to a good solution by applying list scheduling as a decoding heuristic. The proposed technique is an effective method that yields good results without problem-specific parameter tuning on test problems. We demonstrate the effectiveness of our technique by comparing it with the existing microcode compaction techniques for randomly generated data dependency graphs. The proposed scheme offers considerable improvement in the number of microinstructions compared with the existing techniques with comparable cpu time.
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一种基于进化的局部微码压缩技术
在本文中,我们提出了一种局部微码压缩模拟进化技术的变体。模拟进化是一种基于类比生物进化中的自然选择过程的一般优化方法。该技术将模拟进化与链表调度相结合,利用模拟进化来确定合适的优先级,并将链表调度作为解码启发式算法来得到较好的解决方案。所提出的技术是一种有效的方法,无需对测试问题进行特定的参数调优即可获得良好的结果。通过将我们的技术与现有的用于随机生成数据依赖图的微码压缩技术进行比较,我们证明了该技术的有效性。在cpu时间相当的情况下,与现有技术相比,所提出的方案在微指令数量上有很大的改进。
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