SHF: Small: PAPI-V Hardware Performance Monitoring for Virtualized Environments

云计算涉及使用托管的计算环境，其可以按需提供弹性计算和存储服务。虚拟化是一种允许多个虚拟机（VM）在单个物理机器上运行并共享其资源的技术。虚拟化越来越多地用于云计算，以提供规模经济、定制环境、故障隔离和可靠性。 为了解决将云计算用于科学计算的性能问题，PAPI-V项目正在开发一个虚拟化环境中的硬件性能监测系统，使软件开发人员能够了解和优化系统和应用程序的性能，并适应不断变化的条件。 为了实现这一目标，该项目正在扩展广泛使用的性能API（PAPI）跨平台库，以访问硬件性能计数器。定时：PAPI定时例程正在扩展，以提供跨不同虚拟机网络（VMM）的标准真实的和虚拟定时器。2.组件测量：现有的PAPI I/O、网络和其他共享资源组件正在扩展，以在虚拟化环境中提供相关信息。3.所选处理器硬件计数器的虚拟化：被认为与虚拟化环境中的应用程序性能分析和调优最相关的一组所选处理器计数器正在跨VMM实施。4.数据解释：目前正在开发一种机制，用于定义正确量化各种因素对整体绩效的贡献的度量标准。研究结果将在可供使用和广泛使用的PAPI库中实施。PAPI-V扩展将允许应用程序和工具开发人员使用熟悉的界面来获取相关信息，以便在云计算环境中实现最佳性能。

Cloud computing involves use of a hosted computational environment that can provide elastic compute and storage services on demand. Virtualization is a technology that allows multiple virtual machines (VMs) to run on a single physical machine and share its resources. Virtualization is increasingly being used in cloud computing to provide economies of scale, customized environments, fault isolation, and reliability. To address performance concerns with the use of cloud computing for scientific computing, the PAPI-V project is developing a system for hardware performance monitoring in virtualized environments to enable software developers to understand and optimize system and application performance and adapt to changing conditions. To accomplish this goal, the project is extending the widely used Performance API (PAPI) cross-platform library for accessing hardware performance counters.The PAPI-V project is addressing the following aspects: 1. Timing: The PAPI timing routines are being extended to provide standard real and virtual timers across different Virtual Machine Monitors (VMMs). 2. Component measurements: The existing PAPI I/O, network, and other shared resource components are being extended to provide relevant information in virtualized environments. 3. Virtualization of selected processor hardware counters: A selected set of processor counters considered being most relevant for application performance analysis and tuning in virtualized environments is being implemented across VMMs. 4. Interpretation of data: A mechanism for defining metrics that correctly quantify the contributions of various factors to overall performance is under development.The research results will be implemented in the publically available and widely used PAPI library. The PAPI-V extension will allow application and tool developers to use a familiar interface to obtain relevant information for achieving the best possible performance in cloud computing environments.