High Frequency Performance Monitoring via Architectural Event Measurement

Chutitep Woralert, James Bruska, Chen Liu, Lok K. Yan
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引用次数: 4

Abstract

Obtaining detailed software execution information via hardware performance counters is a powerful analysis technique. The performance counters provide an effective method to monitor program behaviors; hence performance bottlenecks due to hardware architecture or software design and implementation can be identified, isolated and improved on. The granularity and overhead of the monitoring mechanism, however, are paramount to proper analysis. Many prior designs have been able to provide performance counter monitoring with inherited drawbacks such as intrusive code changes, a slow timer system, or the need for a kernel patch. In this paper, we present K-LEB (Kernel - Lineage of Event Behavior), a new monitoring mechanism that can produce precise, non-intrusive, low overhead, periodic performance counter data using a kernel module based design. Our proposed approach has been evaluated on three different case studies to demonstrate its effectiveness, correctness and efficiency. By moving the responsibility of timing to kernel space, K-LEB can gather periodic data at a 100μs rate, which is 100 times faster than other comparable performance counter monitoring approaches. At the same time, it reduces the monitoring overhead by at least 58.8%, and the difference between the recorded performance counter readings and those of other tools are less than 0.3%.
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通过架构事件度量进行高频性能监控
通过硬件性能计数器获取详细的软件执行信息是一种强大的分析技术。性能计数器提供了一种有效的方法来监控程序行为;因此,由于硬件架构或软件设计和实现造成的性能瓶颈可以被识别、隔离和改进。然而,监视机制的粒度和开销对于正确的分析是至关重要的。许多先前的设计已经能够提供性能计数器监视,但存在一些固有的缺点,例如侵入性代码更改、慢计时器系统或需要内核补丁。在本文中,我们提出了K-LEB (Kernel - Lineage of Event Behavior),这是一种新的监控机制,可以使用基于内核模块的设计产生精确的、非侵入性的、低开销的、周期性的性能计数器数据。我们提出的方法已经在三个不同的案例研究中进行了评估,以证明其有效性,正确性和效率。通过将计时的责任转移到内核空间,K-LEB可以以100μs的速率收集周期性数据,这比其他类似的性能计数器监控方法快100倍。同时,它减少了至少58.8%的监视开销,并且记录的性能计数器读数与其他工具的读数之间的差异小于0.3%。
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