The purpose of the PAPI project is to specify a standard application programming interface (API) for accessing hardware performance counters available on most modern microprocessors. These counters exist as a small set of registers that count events, which are occurrences of specific signals and states related to the processor s function. Monitoring these events facilitates correlation between the structure of source/object code and the efficiency of the mapping of that code to the underlying architecture. This correlation has a variety of uses in performance analysis including hand tuning, compiler optimization, debugging, benchmarking, monitoring and performance modeling. In addition, it is hoped that this information will prove useful in the development of new compilation technology as well as in steering architectural development towards alleviating commonly occurring bottlenecks in high performance computing.

The purpose of the PAPI project is to specify a standard API for accessing hardware performance counters available on most modern microprocessors. These counters exist as a small set of registers that count "events", which are occurrences of specific signals and states related to the processor's function. Monitoring these events facilitates correlation between the structure of source/object code and the efficiency of the mapping of that code to the underlying architecture. This correlation has a variety of uses in performance analysis and tuning. The PAPI project has proposed a standard set of hardware events and a standard cross-platform library interface to the underlying counter hardware. The PAPI library has been or is in the process of being implemented on all major HPC platforms. The PAPI project is developing end-user tools for dynamically selecting and displaying hardware counter performance data. PAPI support is also being incorporated into a number of third-party tools.

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The PAPI project has defined and implemented a crossplatform interface to the hardware counters available on most modern microprocessors. The interface has gained widespread use and acceptance from hardware vendors, users, and tool developers. This paper reports on experiences with the community-based open-source effort to define the PAPI specification and implement it on a variety of platforms. Collaborations with tool developers who have incorporated support for PAPI are described. Issues related to interpretation and accuracy of hardware counter data and to the overheads of collecting this data are discussed. The paper concludes with implications for the design of the next version of PAPI.

Abstract-This paper describes extensions to the PAPI hardware counter library for virtual environments, called PAPI-V. The extensions support timing routines, I/O measurements, and processor counters. The PAPI-V extensions will allow application and tool developers to use a familiar interface to obtain relevant hardware performance monitoring information in virtual environments. Keywords-performance counters; virutal machines; performance analsis; performance monitoring I.INTRODUCTION 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) crossplatform library [PAPI] for accessing hardware performance counters [1].