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Numerical strategies towards peta-scale simulations of nanoelectronics devices

机译:纳米电子设备超大规模仿真的数值策略

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We address two challenges with the development of next-generation nanotransistors, (ⅰ) the capability of modeling realistically extended structures on an atomistic basis and (ⅱ) predictive simulations that are faster and cheaper than experiments. We have developed a multi-dimensional, quantum transport solver, OMEN, towards these goals. To approach the peta-scale, the calculation of the open boundary conditions connecting the simulation domain to its environment is interleaved with the computation of the device wave functions and the work load of each task is predicted prior to any calculation, resulting in a dynamic core allocation. OMEN uses up to 147,456 cores on Jaguar with four levels of MPI parallelization and reaches a sustained performance of 504 TFlop/s, running at 37% of the machine peak performance. We investigate 3D nanowire transistors with diameters up to 10nm, reproduce experimental data of high electron mobility 2D transistors, and expect increased capabilities by using over 300,000 cores in the future.
机译:随着下一代纳米晶体管的发展,我们解决了两个挑战:(ⅰ)在原子基础上对现实扩展的结构进行建模的能力以及(ⅱ)比实验更快,更便宜的预测性仿真。我们已针对这些目标开发了多维量子传输求解器OMEN。为了达到Peta规模,将模拟域连接到其环境的开放边界条件的计算与设备波动函数的计算交织在一起,并且在进行任何计算之前都要预测每个任务的工作量,从而形成动态核心分配。 OMEN在Jaguar上使用多达147,456个内核,并具有四个级别的MPI并行化,并达到504 TFlop / s的持续性能,运行速度是机器峰值性能的37%。我们研究了直径最大为10nm的3D纳米线晶体管,再现了高电子迁移率2D晶体管的实验数据,并期望将来通过使用超过300,000个内核来提高功能。

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