Continuous profiling: where have all the cycles gone?

Jennifer M. Anderson, Lance M. Berc, J. Dean, S. Ghemawat, Monika Henzinger, Shun-Tak Leung, R. L. Sites, Mark T. Vandevoorde, Carl A. Waldspurger, W. Weihl
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引用次数: 36

Abstract

This paper describes the DIGlTAL Continuous Profiling Infrastmcture, a sampling-based profiling system designed to run continuously on production systems. The system supports multiprocessors, works on unmodified executable& and collects profiles for entire systems, including user programs, shared libraries, and the operating system kernel. Samples are collected at a high rate (over 5200 samples/secper333-MHz processor), yet with low overhead (l-3% slowdown for most workloads). Analysis tools supplied with the profiling system use the sample data to produce an accurate accounting, down to the level of pipeline stalls incurred by individual instructions, of where time is being spent. When instructions incur stalls, the tools identify possible reasons, such as cache misses, branch mispredictions, and functional unit contention. The fine-grained instruction-level analysis guides users and automated optimizers to the causes of performance problems and provides important insights for fixing them.
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连续分析:所有的周期都去了哪里?
本文介绍了digtal连续分析基础设施,这是一个基于采样的分析系统,旨在在生产系统上连续运行。该系统支持多处理器,在未修改的可执行文件&上工作,并收集整个系统的配置文件,包括用户程序、共享库和操作系统内核。样本的收集速率很高(超过5200个样本/每个333- mhz处理器),但开销很低(对于大多数工作负载来说,速度会降低l-3%)。分析系统提供的分析工具使用样本数据来产生准确的会计,直至单个指令导致的管道延误水平,以及时间的花费。当指令发生停顿时,工具会识别可能的原因,例如缓存丢失、分支预测错误和功能单元争用。细粒度指令级分析指导用户和自动优化器找到性能问题的原因,并为修复这些问题提供重要的见解。
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