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A performance counter architecture for computing accurate CPI components

机译:用于计算精确CPI组件的性能计数器架构

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A common way of representing processor performance is to use Cycles per Instruction (CPI) `stacks' which break performance into a baseline CPI plus a number of individual miss event CPI components. CPI stacks can be very helpful in gaining insight into the behavior of an application on a given microprocessor; consequently, they are widely used by software application developers and computer architects. However, computing CPI stacks on superscalar out-of-order processors is challenging because of various overlaps among execution and miss events (cache misses, TLB misses, and branch mispredictions).This paper shows that meaningful and accurate CPI stacks can be computed for superscalar out-of-order processors. Using interval analysis, a novel method for analyzing out-of-order processor performance, we gain understanding into the performance impact of the various miss events. Based on this understanding, we propose a novel way of architecting hardware performance counters for building accurate CPI stacks. The additional hardware for implementing these counters is limited and comparable to existing hardware performance counter architectures while being significantly more accurate than previous approaches.
机译:表示处理器性能的常用方式是使用每个指令(CPI)的周期(CPI)“堆栈”,将性能中断到基线CPI加上许多单独的错误事件CPI组件。 CPI堆栈对获得给定微处理器上应用程序的行为非常有帮助;因此,它们被软件应用程序开发人员和计算机架构师广泛使用。但是,在Superscalar超出订处的计算CPI堆栈是具有挑战性的,因为执行和错误事件中的各种重叠(缓存未命中,TLB未命中和分支错误预测)。这篇论文显示了用于Superscalar的有意义和准确的CPI堆栈无序处理器。使用间隔分析,一种用于分析无序处理器性能的新方法,我们获得了对各种错误事件的性能影响的理解。基于此理解,我们提出了一种新的架构硬件性能计数器的新方法,用于构建精确的CPI堆栈。用于实现这些计数器的附加硬件是有限的,并且与现有的硬件性能计数器架构相当,同时显着比以前的方法更准确。

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