计算机应用与软件
計算機應用與軟件
계산궤응용여연건
Computer Applications and Software
2015年
8期
117-120,126
,共5页
遗传算法%网络处理器%任务分配%流水线
遺傳算法%網絡處理器%任務分配%流水線
유전산법%망락처리기%임무분배%류수선
Genetic algorithm(GA)%Network processor%Task allocation%Pipeline
流水线模式是网络处理器常用的一种编程模式，将任务映射到处理器处理引擎上去是NP-完全问题。针对以往基于遗传算法的解决方案过早收敛的局限性，提出mGaPipe算法。该算法采用优化交叉算子IMX和混合变异算子HybridM，避免遗传算法出现过早收敛，从而显著提高遗传算法解决此类问题的准确度。仿真结果显示mGaPipe算法在同等条件下将收敛到最优解的比率从传统遗传算法的解决方案的9．25％提升到52．25％。
流水線模式是網絡處理器常用的一種編程模式，將任務映射到處理器處理引擎上去是NP-完全問題。針對以往基于遺傳算法的解決方案過早收斂的跼限性，提齣mGaPipe算法。該算法採用優化交扠算子IMX和混閤變異算子HybridM，避免遺傳算法齣現過早收斂，從而顯著提高遺傳算法解決此類問題的準確度。倣真結果顯示mGaPipe算法在同等條件下將收斂到最優解的比率從傳統遺傳算法的解決方案的9．25％提升到52．25％。
류수선모식시망락처리기상용적일충편정모식，장임무영사도처리기처리인경상거시NP-완전문제。침대이왕기우유전산법적해결방안과조수렴적국한성，제출mGaPipe산법。해산법채용우화교차산자IMX화혼합변이산자HybridM，피면유전산법출현과조수렴，종이현저제고유전산법해결차류문제적준학도。방진결과현시mGaPipe산법재동등조건하장수렴도최우해적비솔종전통유전산법적해결방안적9．25％제승도52．25％。
Pipelined pattern is a generally usable programming pattern of network processors, and to map the tasks onto the processing engine of processor is an NP-Complete problem.But previous GA-based solution has some limitations, such as premature convergence.In light of this, we proposed an mGaPine algorithm.This algorithm adopts the optimised crossover operator ( IMX) and the hybrid mutation operator ( HybridM) and prevents the GA from being premature convergence, so that significantly improves the precision of GA in solving similar problems.Simulation results indicated that the mGaPipe algorithm raised the ratio of converging to best solution from 9.25% of the solution of traditional genetic algorithm to 52.25%.
