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GPU-based parallelization for fast circuit optimization

机译:基于GPU的并行化可实现快速电路优化

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The progress of GPU (Graphics Processing Unit) technology opens a new avenue for boosting computing power. This work is an attempt to exploit GPU for accelerating VLSI circuit optimization. We propose GPU-based parallel computing techniques and apply them on simultaneous gate sizing and threshold voltage assignment, which is often employed in practice for performance and power optimization. These techniques are aimed to fully utilize the benefits of GPU through efficient task scheduling and memory organization. Compared to conventional sequential computation, our techniques can provide up to 56x speedup without any sacrifice on solution quality.
机译:GPU(图形处理单元)技术的进步为增强计算能力开辟了一条新途径。这项工作是尝试利用GPU来加速VLSI电路优化。我们提出了基于GPU的并行计算技术,并将其应用于同时进行的栅极大小调整和阈值电压分配,这在实践中经常用于性能和功耗优化。这些技术旨在通过有效的任务调度和内存组织来充分利用GPU的优势。与传统的顺序计算相比,我们的技术可以提供高达56倍的加速,而不会牺牲解决方案的质量。

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