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Boosting the 3D thermal-aware floorplanning problem through a master-worker parallel MOEA

机译:通过主工人并行MOEA促进3D热感知平面规划问题

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摘要

The increasing transistor scale integration poses, among others, the thermal-aware floorplanning problem consisting of how to place the hardware components in order to reduce overheating by dissipation. Because of the huge amount of feasible floorplans, most of the solutions found in the literature include an evolutionary algorithm for, either partially or completely, carrying out the task of floorplanning. Evolutionary algorithms usually have a bottleneck in the fitness evaluation. In the problem of thermal-aware floorplanning, the layout evaluation by the thermal model takes 99.5% of the computational time for the best floorplanning algorithm proposed so far. The contribution of this paper is to present a parallelization of this evaluation phase in a master-worker model to achieve a dramatic speed-up of the thermal-aware floorplanning process. Exhaustive experimentation was carried out over 3D integrated circuits, with 48 and 128 cores, outperforming previous published works.
机译:日益增加的晶体管规模集成带来了热感知平面规划问题,其中包括如何放置硬件组件以减少由于散热引起的过热。由于存在大量可行的平面布置图,因此文献中发现的大多数解决方案都包括一种用于部分或完全执行平面布置图任务的进化算法。进化算法通常在适应性评估中存在瓶颈。在热敏布局规划问题中,对于目前提出的最佳布局规划算法,通过热模型进行布局评估需要占用计算时间的99.5%。本文的贡献是在主工人模型中提出了该评估阶段的并行化,以实现热感知布局规划过程的显着加速。在具有48和128核的3D集成电路上进行了详尽的实验,优于以前发表的作品。

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