线程映射在软硬件仿真中的不确定性影响

G. Salvador, Siddharth Nilakantan, B. Taskin, Mark Hempstead, A. More
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引用次数: 1

摘要

在本文中,我们探讨了蒙特卡罗设计空间探索下多线程程序和线程映射的仿真性能权衡。这项探索使用的工具将是最近的一项研究,该研究将其新颖的基于Google Page rank的线程映射方法与数百个随机映射进行比较,以及在类似比较中使用的论文中提出的基于轮询的线程映射方法。现代模拟器领域呈现出周期精确但速度缓慢和快速但速度不准确的程序模拟之间的选择。我们发现,使用快速,不准确的多线程模拟器,如Sniper 5.3,在报告的程序性能中存在很大的不确定性。我们执行周期精确的仿真,这表明静态线程映射方法确实在达到接近最佳设计点方面提供了好处。此外,与使用完整的蒙特卡罗方法探索映射设计点相比,使用周期精确的模拟器可以显著减少静态线程映射的运行时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effects of Nondeterminism in Hardware and Software Simulation with Thread Mapping
In this paper, we explore the simulation performance trade-off under the lens of Monte Carlo design space exploration for multi-threaded programs and thread mapping. The vehicle used for this exploration will be a recent study, whose novel Google Page Rank-based thread mapping approach is compared to hundreds of random mappings, as well as a Round-Robin-based thread mapping approach proposed in this paper used in similar comparisons. The modern simulator landscape presents a choice between cycle-accurate but slow, and fast but inaccurate program simulation. We find that the use of a fast, inaccurate multi-threaded simulator, such as Sniper 5.3, suffers from large nondeterminism in the reported performance of the program. We perform cycle-accurate simulation which demonstrates that the static thread mapping approach does provide benefits in reaching near-optimal design points. Furthermore, the runtime of static thread mapping is significantly reduced using a cycle-accurate simulator compared to the full Monte Carlo exploration of mapping design points.
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