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Algorithms for Parallel Simulation of Large-Scale DEVS and Cell-DEVS Models.

机译：大规模DEVS和Cell-DEVS模型的并行仿真算法。

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摘要

The Discrete Event System Specification (DEVS) provides a general methodology for hierarchical construction of reusable models in a modular way and has been used to simulate sophisticated systems in a variety of domains. This dissertation addresses software design and performance issues that arise in parallel simulation of large-scale DEVS-based models on both multiprocessor clusters and chip-multiprocessor architectures.;To address the limitations of microprocessor performance, the industry is moving towards multicore chip-multiprocessor designs. As a latest example of this trend, the IBM Cell processor has attracted a growing interest from the modeling and simulation community. However, general-purpose PDES on such platform requires innovative redesign of existing algorithms in return for better simulation performance. To this end, a new computing technique called Multicore Acceleration of DEVS Systems (MADS) is developed for high-performance parallel DEVS simulation on the Cell processor, combining multi-grained parallelism and various optimizations to overcome the major performance bottlenecks, while hiding, to a great extent, the technical details of multicore programming from general users. Through the concept of LP virtualization, the MADS technique explicitly exploits the massive data- and event-level parallelism inherent in the simulation, making the achievable performance gain more deterministic and predictable than the traditional LP-oriented approaches. Promising results have been produced in the experiments, demonstrating that the MADS technique can be used to accelerate both memory-bound and compute-bound computational kernels in demanding parallel DEVS simulations. The proposed technique not only allows a broad community of DEVS users to tap the potential of the Cell processor with a minimal knowledge of the multicore execution environment, but also makes it possible to integrate cluster-based parallel simulation with multicore-accelerated parallel simulation on hybrid supercomputers.;The Time Warp (TW) mechanism is the most well-known optimistic synchronization protocol for Parallel Discrete-Event Simulations (PDES) . With the increasing scale and complexity, TW simulations face new challenges in terms of excessive memory consumption and operational overhead. In an effort to alleviate these problems, a novel Lightweight Time Warp (LTW) protocol is proposed for efficient optimistic parallel DEVS simulation on multiprocessor clusters. By exploring the intrinsic computational properties of DEVS-based simulations, the LTW protocol allows purely optimistic parallel simulation to be driven by only a few full-fledged TW Logical Processes (LPs), while most of the LPs are set free from the burden of TW execution. The experimental results indicate that simulation performance can be improved significantly in various aspects, including shortened execution time, reduced memory footprint, lowered operational overhead, accelerated event queue operations, facilitated process migration, and enhanced system stability and scalability.
机译：离散事件系统规范（DEVS）提供了用于以模块化方式对可重用模型进行分层构建的通用方法，并且已被用于模拟各种领域中的复杂系统。本文解决了在多处理器集群和芯片-多处理器体系结构上大规模基于DEVS的模型的并行仿真中出现的软件设计和性能问题。为了解决微处理器性能的局限性，业界正朝着多核芯片-多处理器设计的方向发展。 。作为这种趋势的最新示例，IBM Cell处理器引起了建模和仿真社区的越来越多的关注。但是，这种平台上的通用PDES需要对现有算法进行创新性的重新设计，以换取更好的仿真性能。为此，开发了一种称为DEVS系统的多核加速（MADS）的新计算技术，用于在Cell处理器上进行高性能并行DEVS仿真，结合了多粒度并行和各种优化来克服主要的性能瓶颈，同时隐藏起来，很大程度上，来自一般用户的多核编程的技术细节。通过LP虚拟化的概念，MADS技术显式地利用了仿真中固有的海量数据和事件级并行性，从而使可实现的性能比传统的面向LP的方法更具确定性和可预测性。实验产生了可喜的结果，表明MADS技术可用于加速要求并行DEVS仿真的内存绑定和计算绑定计算内核。所提出的技术不仅允许广泛的DEVS用户社区以对多核执行环境的最少了解来挖掘Cell处理器的潜力，而且还可以将基于集群的并行仿真与混合的多核加速并行仿真集成在一起时间扭曲（TW）机制是并行离散事件模拟（PDES）中最著名的乐观同步协议。随着规模和复杂性的增加，TW模拟在过多的内存消耗和操作开销方面面临着新的挑战。为了缓解这些问题，提出了一种新颖的轻量级时间扭曲（LTW）协议，用于在多处理器集群上进行有效的乐观并行DEVS仿真。通过探究基于DEVS的模拟的内在计算特性，LTW协议允许仅由几个成熟的TW逻辑过程（LP）驱动纯粹乐观的并行模拟，而大多数LP则不受TW的负担执行。实验结果表明，仿真性能可以在各个方面得到显着改善，包括缩短执行时间，减少内存占用，降低操作开销，加快事件队列操作，促进进程迁移以及增强系统稳定性和可伸缩性。

著录项

  • 作者

    Liu, Qi.;

  • 作者单位

    Carleton University (Canada).;

  • 授予单位 Carleton University (Canada).;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 185 p.
  • 总页数 185
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:37:32

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