Towards highly optimized cartesian genetic programming: from sequential via SIMD and thread to massive parallel implementation
Towards highly optimized cartesian genetic programming: from sequential via SIMD and thread to massive parallel implementation
复制标题
迈向高度优化的笛卡尔遗传编程：从通过 SIMD 和线程的顺序到大规模并行实现
DOI：
10.1145/2576768.2598343
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
L. Sekanina
中科院分区：
文献类型：
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作者：
Radek Hrbacek;L. Sekanina
在文献中可以找到的笛卡尔遗传规划（CGP）的大多数实现是顺序的。然而，通过遗传编程解决复杂的设计问题需要并行实现的搜索方法和适应度函数。本文论述了CGP的高度优化实现的设计及其在进化电路设计任务中的详细评估。CGP的几个顺序实现进行了分析和各种额外的优化的效果进行了研究。此外，在指令，数据，线程和进程级的并行性已被应用，以利用现代处理器架构和计算机集群。组合加法器和乘法器已被选择，以提供与最先进的方法的性能比较。
Most implementations of Cartesian genetic programming (CGP) which can be found in the literature are sequential. However, solving complex design problems by means of genetic programming requires parallel implementations of search methods and fitness functions. This paper deals with the design of highly optimized implementations of CGP and their detailed evaluation in the task of evolutionary circuit design. Several sequential implementations of CGP have been analyzed and the effect of various additional optimizations has been investigated. Furthermore, the parallelism at the instruction, data, thread and process level has been applied in order to take advantage of modern processor architectures and computer clusters. Combinational adders and multipliers have been chosen to give a performance comparison with state of the art methods.
DOI：
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发表时间：
2002
期刊：
Proceedings of 2002 International Symposium on New Paradigm VLSI Computing
影响因子：
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作者：
Xiaohong Jiang;Pin-Han Ho;Hong Shen;Susumu Horiguchi;Naofumi Homma
通讯作者：
Naofumi Homma