
›› 2017,Vol. 32 ›› Issue (2): 340355.doi: 10.1007/s1139001717142
所属专题： Computer Architecture and Systems； Artificial Intelligence and Pattern Recognition； Software Systems
• Special Section on Selected Paper from NPC 2011 • 上一篇 下一篇
XiaoHu Yan, Member, CCF, FaZhi He^{*}, Member, CCF, YiLin Chen
XiaoHu Yan, Member, CCF, FaZhi He^{*}, Member, CCF, YiLin Chen
随着嵌入式系统设计复杂度的增加，软硬件划分已成为软硬件协同设计中的关键优化难题。文中提出基于野草扰动粒子群算法（Position Disturbed Particle Swarm Optimization with Invasive Weed Optimization，PDPSOIWO）的新型软硬件划分方法。当地松鼠察觉到有潜在捕食者的时候，就会发出警告信息，通知同类远离危险。在PDPSO中，通过模拟这种智能行为，粒子远离群体中全局最差的个体，保持种群多样性，以减少陷入局部最优的可能性。通过改进野草算法（Invasive Weed Optimization，IWO）的初始化和繁殖策略，将IWO集成到PDPSOIWO中，以提高算法在当前全局最优解附近的搜索精度。将PDPSO和改进的IWO融合为PDPSOIWO算法，能同时增强搜索的多样性和集中性。提出HNodeRank方法用于初始化PDPSOIWO的种群，能进一步提升解的质量。由于软硬划分算法中最耗时的过程是计算软硬件的通信代价，文中采用GPU加速该过程，从而能有效减少求解大规模软硬件划分问题的运行时间。最后，通过基准任务和特大规模任务测试集验证了本文方法的有效性。
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