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题名:
并行计算模型参数动态采集分析软件工具包DEMPAT的设计初探
作者: 王向前
答辩日期: 2008-06-05
授予单位: 中国科学院软件研究所
授予地点: 软件研究所
学位: 博士
关键词: 并行计算模型 ; 基准测试程序 ; 机器参数 ; 存储层次 ; PAPI
其他题名: Design and Implementation of a Dynamic Acquisition and Analysis Toolkit for Parallel Computational Model Parameters
摘要: 根据目标平台体系结构尤其是存储系统组织结构的差异,并行计算模型可以分成三代:共享存储并行计算模型、分布存储并行计算模型和层次存储并行计算模型。并行计算模型从第一代发展到第三代的过程中引入了越来越多的模型参数,而且随着处理器与存储系统之间速度差的不断增大,把存储层次引入并行计算模型成为一个新的发展趋势。这在提高模型分析精确度的同时也导致了模型的分析工作越来越复杂,因此有必要设计一个能够对并行计算模型参数进行半自动的获取和分析工具包,以便辅助模型分析工作。 本文首先介绍并行计算模型的发展过程和每个模型涉及到的模型参数,在此基础上提出了我们的并行计算模型参数动态采集分析软件工具包(DEMPAT)及其整体框架,并对现有的基准测试工具进行了简要介绍。我们着重分析了存储层次参数采集模块的设计理论和方法,实现了基于PAPI的高速缓存和TLB参数采集工具,并在主流的平台上进行了相关实验。另外我们采集了两种三角矩阵求逆算法的动态访存行为和浮点运算次数,揭示了存储访问复杂性对算法性能的影响。从实验结果可以看出我们的采集工具具有较好的可用性和精确性,可以作为并行计算模型参数动态采集分析工具中一个重要的组成部分。
英文摘要: The parallel computational model can be classified into three generations according to the targeting architecture, especially the memory organization. They are shared memory parallel computational model, distributed memory parallel computational model and hierarchical memory parallel computational model. With the development of parallel computing systems, more and more parameters are integrated into the parallel computational models. With the ever increasing speed gap between CPU and memory systems, incorporating the non-uniform memory hierarchy becomes a new trend. This increases the accuracy of model analysis while at the same time complicates the analysis, so it is necessary to develop a toolkit to acquire and analyze the model parameters automatically which can be used to aid the model analysis. This thesis first gives brief introduction to the development of parallel computational models and their relevant parameters. We show the framework of our dynamic acquisition and analysis toolkit of parallel computational model parameters: Dynamic Execution and Machine Parameter Analysis Toolkit (DEMPAT). Then we introduce some representative micro-benchmarks. The theory and method which can be used in the design of our memory hierarchy parameter acquisition module is discussed and a PAPI-based cache and TLB parameters acquisition tool is implemented. To reveal the performance impact of memory access complexity, we also compare the dynamic memory access and floating point operations between two kinds of algorithm of triangular matrix reversion. We make experiments on the mainstream platform and it shows that our acquisition tool has good usability and accuracy and can act as an important part in our DEMPAT toolkit.
语种: 中文
内容类型: 学位论文
URI标识: http://ir.iscas.ac.cn/handle/311060/7576
Appears in Collections:并行计算实验室 _学位论文

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Recommended Citation:
王向前. 并行计算模型参数动态采集分析软件工具包DEMPAT的设计初探[D]. 软件研究所. 中国科学院软件研究所. 2008-06-05.
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