首页> 外文会议>2nd joint WOSP/SIPEW international conference on performance engineering 2011 >Characterization, Monitoring and Evaluation of Operational Performance Trends on Server Processor Hardware
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Characterization, Monitoring and Evaluation of Operational Performance Trends on Server Processor Hardware

机译:服务器处理器硬件的运行性能趋势的表征,监视和评估

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Enterprise IT environments have seen a sharp growth in content use due to the popularity of on-demand data-intensive applications. In turn, the huge demand in content has spawne< off major developments such as growth and distribution of computing nodes as well as the adoption of various implementation technologies. Given the complexity brought to the makeup of business computing environments in addressing the above-mentioned factors, the critical planning task of determining the appropriate infrastructure sizes for supporting firm Quality of Service (QoS) guarantees becomes a very challenging undertaking to fulfil. Benchmarking methods are widely employed in calibrating attainable performance in IT solutions, but these have the drawback of presenting output performance metrics as composite measurements that only give an end-to-end perspective. As an enhancement to benchmarking approaches, we explore the use of Performance Monitoring Counters (PMCs) in obtaining detailed operational performance of CPU and memory hardware. Performance Monitoring Counters (PMCs) are on-chip registers found on most modern processor hardware. We use PMC-derived measurements to validate cache performance trends that have been derived analytically, and in the course of validations, PMC data is also used to investigate the nature and character of surges in cache miss events,
机译:由于点播数据密集型应用程序的普及,企业IT环境的内容使用量急剧增长。反过来,对内容的巨大需求使诸如计算机节点的增长和分布以及采用各种实现技术之类的重大发展逐渐消失。考虑到解决上述因素给业务计算环境构成带来的复杂性,确定合适的基础架构大小以支持公司的服务质量(QoS)保证的关键计划任务变得非常具有挑战性。基准测试方法广泛用于校准IT解决方案中的可达到的性能,但是这些方法的缺点是无法将输出性能指标表示为仅提供端到端视角的复合测量。作为对基准测试方法的增强,我们探索了性能监控计数器(PMC)的使用,以获取CPU和内存硬件的详细运行性能。性能监视计数器(PMC)是大多数现代处理器硬件上的片上寄存器。我们使用源自PMC的度量来验证通过分析得出的缓存性能趋势,并且在验证过程中,PMC数据还用于调查缓存未命中事件激增的性质和特征,

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