ScaleSimulator:用于架构探索的快速且周期精确的并行模拟器

Chalak Ori, W. Cai, Wei Li, Lei Fang, Libing Zheng, Jintang Wang, Zuguang Wu, Xiongli Gu, Haibin Wang, A. Mendelson
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引用次数: 0

摘要

下一代计算机系统的设计应得到仿真基础设施的支持,这些基础设施必须实现一些相互矛盾的目标,如快速执行时间、高精度和足够的灵活性,以便在大量可能的设计点之间进行比较。现有的大多数架构级仿真器都设计得非常灵活,并能并行执行代码以提高效率,但其代价是降低精度。本文介绍了 ScaleSimulator 仿真环境,它基于一种新的设计方法,其目标是实现接近周期的精度,同时具有足够的灵活性来仿真许多不同的未来系统架构,并具有足够的效率来运行有意义的工作负载。我们通过让并行性成为我们方法中的一等公民来实现这些目标。因此,本文主要关注 ScaleSimulator 的设计要点,即在保持仿真架构的可扩展性和周期准确性的同时,实现更好的并行执行。本文指出,新提出的 ScaleSimulator 工具可以:(1) 高效地并行执行周期精确的架构模拟器;(2) 高效地模拟复杂架构(如无序 CPU 管线、高速缓存一致性协议和网络)和大规模并行系统;(3) 使用有意义的工作负载(如全面模拟 OLTP 基准)来检验未来的架构选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ScaleSimulator: A Fast and Cycle-Accurate Parallel Simulator for Architectural Exploration
Design of next generation computer systems should be supported by simulation infrastructure that must achieve a few contradictory goals such as fast execution time, high accuracy, and enough flexibility to allow comparison between large numbers of possible design points. Most existing architecture level simulators are designed to be flexible and to execute the code in parallel for greater efficiency, but at the cost of scarified accuracy. This paper presents the ScaleSimulator simulation environment, which is based on a new design methodology whose goal is to achieve near cycle accuracy while still being flexible enough to simulate many different future system architectures and efficient enough to run meaningful workloads. We achieve these goals by making the parallelism a first-class citizen in our methodology. Thus, this paper focuses mainly on the ScaleSimulator design points that enable better parallel execution while maintaining the scalability and cycle accuracy of a simulated architecture. The paper indicates that the new proposed ScaleSimulator tool can (1) efficiently parallelize the execution of a cycle-accurate architecture simulator, (2) efficiently simulate complex architectures (e.g., out-of-order CPU pipeline, cache coherency protocol, and network) and massive parallel systems, and (3) use meaningful workloads, such as full simulation of OLTP benchmarks, to examine future architectural choices.
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