Towards Scalable Cross-Platform Application Performance Analysis -- Tool Goals and Progress

1. Towards Scalable Cross-Platform Application Performance Analysis -- Tool Goals and Progress Shirley Moore shirley@cs.utk.edu LACSI Symposium, Santa Fe, NM

2. Scalability Issues • Code instrumentation • Hand instrumentation too tedious for large codes • Runtime control of data collection • Batch queueing systems • Cause problems for interactive tools • Tracefile size and complexity • Data analysis LACSI Symposium, Santa Fe, NM

3. Cross-platform Issues • Goal: similar user interfaces across different platforms • Tools necessarily rely on platform-dependent substrates – e.g., for accessing hardware counters. • Standardization of interfaces and data formats promotes interoperability and allows design of portable tools. LACSI Symposium, Santa Fe, NM

4. Where is Standardization Needed? • Performance data • Trace records vs. summary statistics • Data format • Data semantics • Library interfaces • Access to hardware counters • Statistical profiling • Dynamic instrumentation LACSI Symposium, Santa Fe, NM

5. Standardization? (cont.) • User interfaces • Common set of commands • Common functionality • Timing routines • Memory utilization information LACSI Symposium, Santa Fe, NM

6. Parallel Tools Consortium • http://www.ptools.org/ • Interaction between vendors, researchers, and users • Venue for standardization • Current projects • PAPI • DPCL LACSI Symposium, Santa Fe, NM

7. Hardware Counters • Small set of registers that count events, which are occurrences of specific signals related to the processor’s function • Monitoring these events facilitates correlation between the structure of the source/object code and the efficiency of the mapping of that code to the underlying architecture. LACSI Symposium, Santa Fe, NM

8. Goals of PAPI • Solid foundation for cross platform performance analysis tools • Free tool developers from re-implementing counter access • Standardization between vendors, academics and users • Encourage vendors to provide hardware and OS support for counter access • Reference implementations for a number of HPC architectures • Well documented and easy to use LACSI Symposium, Santa Fe, NM

9. PAPI Implementation Tools!!! PAPI Low Level PAPI High Level Portable Layer PAPI Machine Dependent Substrate Machine Specific Layer Kernel Extension Operating System Hardware Performance Counter LACSI Symposium, Santa Fe, NM

10. PAPI Preset Events • Proposed standard set of events deemed most relevant for application performance tuning • Defined in papiStdEventDefs.h • Mapped to native events on a given platform • Run tests/avail to see list of PAPI preset events available on a platform LACSI Symposium, Santa Fe, NM

11. Statistical Profiling • PAPI provides support for execution profiling based on any counter event. • PAPI_profil() creates a histogram by text address of overflow counts for a specified region of the application code. • Used in vprof tool from Sandia Lab LACSI Symposium, Santa Fe, NM

12. Linux/x86, Windows 2000 Requires patch to Linux kernel, driver for Windows Linux/IA-64 Sun Solaris 2.8/Ultra I/II IBM AIX 4.3+/Power Contact IBM for pmtoolkit SGI IRIX/MIPS Compaq Tru64/Alpha Ev6 & Ev67 Requires OS device driver patch from Compaq Per-thread and per-process counts not possible Extremely limited number of events Cray T3E/Unicos PAPI Reference Implementations LACSI Symposium, Santa Fe, NM

13. PAPI Future Work • Improve accuracy of hardware counter and statistical profiling data • Microbenchmarks to measure accuracy (Pat Teller, UTEP) • Use hardware support for overflow interrupts • Use Event Address Registers (EARs) where available • Data structure based performance counters (collaboration with UMd) • Qualify event counting by address range • Page level counters in cache coherence hardware LACSI Symposium, Santa Fe, NM

14. PAPI Future (cont.) • Memory utilization extensions (following list suggested by Jack Horner, LANL) • Memory available on a node • Total memory available/used • High-water-mark memory used by process/thread • Disk swapping by process • Process-memory locality • Location of memory used by an object • Dynamic instrumentation – e.g., PAPI probe modules LACSI Symposium, Santa Fe, NM

15. For More Information • http://icl.cs.utk.edu/projects/papi/ • Software and documentation • Reference materials • Papers and presentations • Third-party tools • Mailing lists LACSI Symposium, Santa Fe, NM

16. DPCL • Dynamic Probe Class Library • Built of top of IBM version of University of Maryland’s dyninst • Current platforms • IBM AIX • Linux/x86 (limited functionality) • Dyninst ported to more platforms but by itself lacks functionality for easily instrumenting parallel applications. LACSI Symposium, Santa Fe, NM

17. Infrastructure Components? • Parsers for common languages • Access to hardware counter data • Communication behavior instrumentation and analysis • Dynamic instrumentation capability • Runtime control of data collection and analysis • Performance data management LACSI Symposium, Santa Fe, NM

18. Case Studies • Test tools on large-scale applications in production environment • Reveal limitations of tools and point out areas where improvements are needed • Develop performance tuning methodologies for large-scale codes LACSI Symposium, Santa Fe, NM

19. PERC: Performance Evaluation Research Center • Developing a science for understanding performance of scientific applications on high-end computer systems. • Developing engineering strategies for improving performance on these systems. • DOE Labs: ANL, LBNL, LLNL, ORNL • Universities: UCSD, UI-UC, UMD, UTK • Funded by SciDAC: Scientific Discovery through Advanced Computing LACSI Symposium, Santa Fe, NM

20. PERC: Real-World Applications • High Energy and Nuclear Physics • Shedding New Light on Exploding Stars: Terascale Simulations of Neutrino-Driven SuperNovae and Their NucleoSynthesis • Advanced Computing for 21st Century Accelerator Science and Technology • Biology and Environmental Research • Collaborative Design and Development of the Community Climate System Model for Terascale Computers • Fusion Energy Sciences • Numerical Computation of Wave-Plasma Interactions in Multi-dimensional Systems • Advanced Scientific Computing • Terascale Optimal PDE Solvers (TOPS) • Applied Partial Differential Equations Center (APDEC) • Scientific Data Management (SDM) • Chemical Sciences • Accurate Properties for Open-Shell States of Large Molecules • …and more… LACSI Symposium, Santa Fe, NM

21. Parallel Climate Transition Model • Components for Ocean, Atmosphere, Sea Ice, Land Surface and River Transport • Developed by Warren Washington’s group at NCAR • POP: Parallel Ocean Program from LANL • CCM3: Community Climate Model 3.2 from NCAR including LSM: Land Surface Model • ICE: CICE from LANL and CCSM from NCAR • RTM: River Transport Module from UT Austin • Fortran 90 with MPI LACSI Symposium, Santa Fe, NM

22. PCTM: Parallel Climate Transition Model RiverModel OceanModel AtmosphereModel Flux Coupler LandSurfaceModel Sea Ice Model Sequential Executionof Parallelized Modules LACSI Symposium, Santa Fe, NM

23. PCTM Instrumentation • Vampir tracefile in tens of gigabytes range even for toy problem • Hand instrumentation with PAPI tedious • UIUC working on SvPablo instrumentation • Must work in batch queueing environment • Plan to try other tools • MPE logging and jumpshot • TAU • VGV? LACSI Symposium, Santa Fe, NM

24. In Progress • Standardization and reference implementations for memory utilization information (funded by DoD HPCMP PET, Ptools-sponsored project) • Repositories of application performance evaluation case studies (e.g., SciDAC PERC) • Portable dynamic instrumentation for parallel applications (DOE MICS project – UTK, UMd, UWisc) • Increased functionality and accuracy of hardware counter data collection (DoD HPCMP, DOE MICS) LACSI Symposium, Santa Fe, NM

25. Next Steps • Additional areas for standardization? • Scalable trace file format • Metadata standards for performance data • New hardware counter metrics (e.g., SMP and DMP events, data-centric counters) • Others? LACSI Symposium, Santa Fe, NM

26. Next Steps (cont.) • Sharing of tools and data • Open source software • Machine and software profiles • Runtime performance data • Benchmark results • Application examples and case studies • Long-term goal: common performance tool infrastructure across HPC systems LACSI Symposium, Santa Fe, NM