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Exploring the Performance Limits of Simultaneous Multithreading for Scientific Codes

机译:探索科学代码的同时多线程性能极限

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Simultaneous multithreading (SMT) has been proposed to improve system throughput by overlapping instructions from multiple threads on a single wide-issue processor. The speedup of a single application that is parallelized into multiple threads, is often sensitive to its inherent instruction level parallelism (ILP), as well as the efficiency of synchronization and communication mechanisms between its separate, but possibly dependent, threads. In this paper, we evaluate and contrast software prefetching and thread-level parallelism (TLP) techniques for a series of scientific codes executed on an SMT processor. We explore the performance limits by evaluating the tradeoffs between ILP and TLP for various kinds of instructions streams. Obtaining knowledge on how such streams interact when executed simultaneously on the processor, and quantifying their presence within each application''s threads, we try to interpret the observed performance for each application when parallelized according to the aforementioned techniques. In order to amplify this evaluation process, we also present results gathered from the performance monitoring hardware of the processor
机译:已经提出了同时多线程(SMT)来通过在单个宽发行处理器上重叠来自多个线程的指令来提高系统吞吐量。并行化为多个线程的单个应用程序的加速通常对其固有的指令级并行性(ILP)以及其单独的(但可能是从属的)线程之间的同步和通信机制的效率很敏感。在本文中,我们评估和对比了在SMT处理器上执行的一系列科学代码的软件预取和线程级并行(TLP)技术。我们通过评估各种指令流在ILP和TLP之间的权衡来探索性能极限。获得有关这些流在处理器上同时执行时如何交互的知识,并量化它们在每个应用程序线程中的存在,我们尝试根据上述技术对每个应用程序并行化时观察到的性能进行解释。为了扩大此评估过程,我们还介绍了从处理器性能监视硬件收集的结果

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