We present a solution of sparse alternating current optimal power flow (ACOPF) analysis on graphical processing unit (GPU). In particular, we discuss the performance bottlenecks and detail our efforts to accelerate the linear solver, a core component of ACOPF that dominates the computational time. ACOPF analyses of two large-scale systems, synthetic Northeast (25,000 buses) and Eastern (70,000 buses) U.S. grids [1], on GPU show promising speed-up compared to analyses on central processing unit (CPU) using a state-of-the-art solver. To our knowledge, this is the first result demonstrating a significant acceleration of sparse ACOPF on GPUs.
翻译：我们提出了一个对图形处理器(GPU)进行零散交替当前最佳电流分析的解决方案。特别是,我们讨论了性能瓶颈问题,并详细介绍了我们加快线性求解器的努力,这是ACOPF在计算时间上占主导地位的核心组成部分。ACOPF对两个大型系统(合成东北(25,000辆公共汽车)和美国东部(70,000辆大客车)[1])的分析显示,与使用最先进的解答器对中央处理器(CPU)的分析相比,GPU的加速速度很有希望。 据我们所知,这是第一个表明在GPU上少见的ACOPF显著加速的结果。
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