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Open MPI - A High Performance Fault Tolerant MPI Library

Open MPI - A High Performance Fault Tolerant MPI Library. Richard L. Graham Advanced Computing Laboratory, Group Leader (acting). Overview. Open MPI Collaboration MPI Run-time Future directions. Los Alamos National Laboratory (LA-MPI) Sandia National Laboratory

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Open MPI - A High Performance Fault Tolerant MPI Library

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  1. Open MPI - A High Performance Fault Tolerant MPI Library Richard L. Graham Advanced Computing Laboratory, Group Leader (acting)

  2. Overview • Open MPI Collaboration • MPI • Run-time • Future directions

  3. Los Alamos National Laboratory (LA-MPI) Sandia National Laboratory Indiana University (LAM/MPI) The University of Tennessee (FT-MPI) High Performance Computing Center, Stuttgart (PACX-MPI) University of Houston Cisco Systems Mellanox Voltaire Sun Myricom IBM QLogic URL: www.open-mpi.org Collaborators

  4. A Convergence of Ideas FT-MPI (U of TN) Open MPI LA-MPI (LANL) LAM/MPI (IU) PACX-MPI (HLRS) OpenRTE Fault Detection (LANL, Industry) FDDP (Semi. Mfg. Industry) Resilient Computing Systems Robustness (CSU) Autonomous Computing (many) Grid (many)

  5. Components • Formalized interfaces • Specifies “black box” implementation • Different implementations available at run-time • Can compose different systems on the fly Caller Interface 1 Interface 2 Interface 3

  6. Performance Impact

  7. MPI

  8. Two Sided Communications

  9. P2P Component Frameworks

  10. Shared Memory - Bandwidth

  11. Shared Memory - Latency

  12. IB PerformanceLatency

  13. IB PerformanceBandwidth

  14. GM Performance DataPing-Pong Latency (usec)

  15. GM Performance DataPing-Pong Latency (usec) - Data FT

  16. GM Performance DataPing-Pong Bandwidth

  17. MX Ping-Pong Latency (usec)

  18. MX Performance DataPing-Pong Bandwidth (MB/sec)

  19. XT3 PerformanceLatency

  20. XT3 PerformanceBandwidth

  21. Collective Operations

  22. MPI Reduce - Performance

  23. MPI Broadcast - Performance

  24. MPI Reduction - II

  25. Open RTE

  26. Open RTE - Design Overview Cluster Seamless, transparent environment for high-performance applications Grid • Inter-process communications within and across cells • Distributed publish/subscribe registry • Supports event-driven logic across applications, cells • Persistent, fault tolerant • Dynamic “spawn” of processes, applications both within and across cells Cluster Single Computer

  27. Open RTE - Components Cluster UNIVERSE Grid Cluster Single Computer

  28. General Purpose Registry • Cached, distributed storage/retrieval system • All common data types plus user-defined • Heterogeneity between storing process and recipient automatically resolved • Publish/subscribe • Support event-driven coordination and notification • Subscribe to individual data elements, groups of elements, wildcard collections • Specify actions that trigger notifications

  29. Subscription Services • Subscribe to container and/or keyval entry • Can be entered before data arrives • Specifies data elements to be monitored • Container tokens and/or data keys • Wildcards supported • Specifies action that generates event • Data entered, modified, deleted • Number of matching elements equals, exceeds, is less than specified level • Number of matching elements transitions (increases/decreases) through specified level • Events generate message to subscriber • Includes specified data elements • Asynchronously delivered to specified callback function on subscribing process

  30. Future Directions

  31. Revise MPI Standard • Clarify standard • Standardized the interface • Simplify standard • Make the standard more “H/W Friendly”

  32. Beyond Simple Performance Measures • Performance and scalability are important, but • What about future HPC systems • Heterogeneity • Multi-core • Mix of processors • Mix of networks • Fault-tolerance

  33. Focus on Programmability • Performance and Scalability are important, but what about • Programmability

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