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Using a Complementary Emulation-Simulation Co-Design Approach to Assess Application Readiness for Processing-in-Memory Systems

机译:使用互补的仿真-仿真协同设计方法评估内存中处理系统的应用程序准备情况

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摘要

Disruptive changes to computer architecture are paving the way toward extreme scale computing. The co-design strategy of collaborative research and development among computer architects, system software designers, and application teams can help to ensure that applications not only cope but thrive with these changes. In this paper, we present a novel combined co-design approach of emulation and simulation in the context of investigating future Processing in Memory (PIM) architectures. PIM enables co-location of data and computation to decrease data movement, to provide increases in memory speed and capacity compared to existing technologies and, perhaps most importantly for extreme scale, to improve energy efficiency. Our evaluation of PIM focuses on three mini-applications representing important production applications. The emulation and simulation studies examine the effects of locality-aware versus locality-oblivious data distribution and computation, and they compare PIM to conventional architectures. Both studies contribute in their own way to the overall understanding of the application-architecture interactions, and our results suggest that PIM technology shows great potential for efficient computation without negatively impacting productivity.
机译:对计算机体系结构的颠覆性变化正在为超大规模计算铺平道路。计算机架构师,系统软件设计师和应用程序团队之间的协作研发共同设计策略可以帮助确保应用程序不仅应对这些变化,而且能够应对这些变化。在本文中,我们在研究未来内存处理(PIM)架构的背景下提出了一种新颖的仿真与仿真联合协同设计方法。与现有技术相比,PIM可以使数据和计算在同一位置,以减少数据移动,提供存储速度和容量的增加,并且也许对于极端规模而言最重要的是提高能源效率。我们对PIM的评估集中在代表重要生产应用程序的三个小型应用程序上。仿真和仿真研究检查了位置感知与位置无关的数据分发和计算的影响,并将PIM与常规体系结构进行了比较。两项研究均以其自己的方式有助于对应用程序-体系结构交互的整体理解,并且我们的结果表明PIM技术显示出有效的计算潜力,而不会负面影响生产率。

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