This project is developing PAPI, which will provide tool designers and application engineers with a consistent interface and methodology for the use of low-level performance counter hardware found across the entire compute system (i.e. CPUs, GPUs, on/off-chip memory, interconnects, I/O system, energy/power, etc.). PAPI will enable users to see, in near real time, the relations between software performance and hardware events across the entire computer system.
Exa-PAPI builds on the latest PAPI project and will be extended with:
The objective is to enable monitoring of both types of performance events—hardware- and software-related events—in a uniform way, through one consistent PAPI interface. Third-party tools and application developers will have to handle only a single hook to PAPI in order to access all hardware performance counters in a system, including the new software-defined events.
Exa-PAPI offers a new PAPI component, called "pcp", which interfaces to the Performance Co-Pilot (PCP). It enables PAPI users to monitor IBM Power9 hardware performance events, particularly shared "NEST" events without root access. We are looking for beta-testers and feedback of the new PAPI PCP component.
For access to the code, follow these steps:
git clone https://bitbucket.org/icl/papi.git
make && make install
|Redesigning PAPIâs High-Level API,” Innovative Computing Laboratory Technical Report, no. ICL-UT-20-03: University of Tennessee, February 2020.“|
|Formulation of Requirements for new PAPI++ Software Package: Part I: Survey Results,” PAPI++ Working Notes, no. No. 1, ICL-UT-20-02: Innovative Computing Laboratory, University of Tennessee Knoxville, January 2020.“|
|PAPI Software-Defined Events for in-Depth Performance Analysis,” The International Journal of High Performance Computing Applications, vol. 33, issue 6, pp. 1113-1127, November 2019.“|
|What it Takes to keep PAPI Instrumental for the HPC Community,” 1st Workshop on Sustainable Scientific Software (CW3S19), Collegeville, Minnesota, July 2019.“|
|Software-Defined Events through PAPI,” 2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), Rio de Janeiro, Brazil, IEEE, May 2019. DOI: 10.1109/IPDPSW.2019.00069“|
|Counter Inspection Toolkit: Making Sense out of Hardware Performance Events,” 11th International Workshop on Parallel Tools for High Performance Computing, Dresden, Germany, Cham, Switzerland: Springer, February 2019. DOI: 10.1007/978-3-030-11987-4_2“|
|Investigating Power Capping toward Energy-Efficient Scientific Applications,” Concurrency Computation: Practice and Experience, vol. 2018, issue e4485, pp. 1-14, April 2018. DOI: 10.1002/cpe.4485“|
|Performance Analysis and Debugging Tools at Scale,” Exascale Scientific Applications: Scalability and Performance Portability: Chapman & Hall / CRC Press, pp. 17-50, November 2017. DOI: 10.1201/b21930“|
|Power-aware Computing: Measurement, Control, and Performance Analysis for Intel Xeon Phi,” 2017 IEEE High Performance Extreme Computing Conference (HPEC'17), Best Paper Finalist, Waltham, MA, IEEE, September 2017.“|
|PAPI's new Software-Defined Events for in-depth Performance Analysis , Dresden, Germany, 13th Parallel Tools Workshop, September 2019.|
|Does your tool support PAPI SDEs yet? , Tahoe City, CA, 13th Scalable Tools Workshop, July 2019.|
|What it Takes to keep PAPI Instrumental for the HPC Community , Collegeville, MN, The 2019 Collegeville Workshop on Sustainable Scientific Software (CW3S19), July 2019.|
|Is your scheduling good? How would you know? , Bordeaux, France, 14th Scheduling for Large Scale Systems Workshop, June 2019.|
|Understanding Native Event Semantics , Knoxville, TN, 9th JLESC Workshop, April 2019.|
|PAPI's New Software-Defined Events for In-Depth Performance Analysis , Lyon, France, CCDSC 2018: Workshop on Clusters, Clouds, and Data for Scientific Computing, September 2018.|
|Software-Defined Events through PAPI for In-Depth Analysis of Application Performance , Basel, Switzerland, 5th Platform for Advanced Scientific Computing Conference (PASC18), July 2018.|
|PAPI: Counting outside the Box , Barcelona, Spain, 8th JLESC Meeting, April 2018.|
Exa-PAPI is part of ICL's involvment in the Exascale Computing Project (ECP). The ECP was established with the goals of maximizing the benefits of high-performance computing (HPC) for the United States and accelerating the development of a capable exascale computing ecosystem. Exascale refers to computing systems at least 50 times faster than the nation’s most powerful supercomputers in use today.
The ECP is a collaborative effort of two U.S. Department of Energy organizations – the Office of Science (DOE-SC) and the National Nuclear Security Administration (NNSA).