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Classifying Performance Bottlenecks in Multi-threaded Applications

机译:分类多线程应用程序中的性能瓶颈

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The performance of multi-threaded applications on modern multi-core processors does not necessarily depend on the number of cores. Instead it depends on multiple factors such as thread synchronization, which leads to thread spinning, and limited memory bandwidth for memory bound applications, which causes cores to wait for requested data and negative references in a shared cache or last-level cache. From a designer's perspective it is important to understand performance bottlenecks of a given application in order to design efficient hardware to achieve optimal performance. In this paper, we propose a model to identify scaling bottlenecks of multi-threaded applications which is based on linear regression. We demonstrate the practical usefulness of the model by applying it to benchmark multi-threaded applications.
机译:现代多核处理器上的多线程应用程序的性能不一定取决于核的数量。取而代之的是,它取决于多个因素,例如线程同步(这会导致线程旋转)以及内存绑定应用程序的有限内存带宽,这会导致内核在共享缓存或最后一级缓存中等待请求的数据和否定引用。从设计人员的角度来看,了解给定应用程序的性能瓶颈对于设计高效的硬件以实现最佳性能非常重要。在本文中,我们提出了一个基于线性回归的模型来确定多线程应用程序的扩展瓶颈。通过将其应用于基准多线程应用程序,我们证明了该模型的实用性。

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