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A Common Application Platform (CAP) for SURAgrid

A Common Application Platform (CAP) for SURAgrid. -Mahantesh Halappanavar, John-Paul Robinson, Enis Afgane, Mary Fran Yafchalk and Purushotham Bangalore. SURAgrid All-hands Meeting, 27 September, 2007, Washington D.C. Introduction. Problem Statement:

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A Common Application Platform (CAP) for SURAgrid

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  1. A Common Application Platform (CAP) for SURAgrid -Mahantesh Halappanavar, John-Paul Robinson, Enis Afgane, Mary Fran Yafchalk and Purushotham Bangalore. SURAgrid All-hands Meeting, 27 September, 2007, Washington D.C.

  2. Introduction • Problem Statement: “How to quickly grid-enable scientific applications to exploit SURAgrid resources ?” • Goals for Grid-enabling Applications: • Dynamic resource discovery • Collective resource utilization • Simple Job Management and Accounting • Minimal Programming Efforts

  3. Identifying Patterns Algorithm Structures Support Structures Relationships

  4. Basic Process Problems Algorithms Programs Implementation Algorithm Structures Supporting Structures Programming Environments

  5. Algorithm Structures How to organize? (Linear and Recursive) • Organize by Tasks • Task Parallelism • Divide and Conquer • Organize by Data Decomposition • Geometric Decomposition • Recursive Data • Organize By Flow of Data • Pipeline • Event-Based Coordination

  6. Program Structures SPMD Master/Worker Loop Parallelism Fork/Join Data Structures Shared Data Shared Queue Distributed Array Support Structures Problems Algorithms Programs Implementation

  7. Relationships: AS and SS Relationship between Supporting Structures (SS) patterns and Algorithm Structure (AS) patterns.

  8. Relationships: SS and PE Relationship between Supporting Structures (SS) patterns and Programming Environments (PE).

  9. Important Observation “This (SPMD) pattern is by far the most commonly used pattern for structuring parallel programs. It is particularly relevant for MPI programmers and problems using the Task Parallelism and Geometric Decomposition patterns. It has also proved effective for problems using the Divide and Conquer, and Recursive Data patterns.” Single Program, Multiple Data (SPMD).This is the most common way to organize a prallel program, especially on MIMD computers. The idea is that a single program is written and loaded onto each node of a parallel computer. Each copy of the single program runs independently (aside from coordination events), so the instruction streams executed on each node can be completely different. The specific path through the code is in part selected by the node ID.

  10. The Computing Continuum OpenMP Java MPI

  11. Scientific Applications What are they? How are they built?

  12. Scientific Applications • Life Sciences: • Biology, Chemistry, … • Engineering: • Aerospace, Civil, Mechanical, Environmental • Physics: • QCD, Black Holes, … • …. The SCaLeS Reports: http://www.pnl.gov/scales/

  13. Building Blocks • OpenMP; MPI; BLACS, … • Metis/ParMetis, Zoltan, Chaco, … • BLAS and LAPACK, … • ScaLapack, MUMPS, SuperLU, … • PETSc, Aztec, … “A core requirement of many engineering and scientific applications is the need to solve linear and non-linear systems of equations, eigensystems and other related problems.” – The Trilinos Project

  14. ScaLAPACK PBLAS Global Local LAPACK BLACS platform specific BLAS MPI/PVM/... ScaLAPACK Parallel BLAS. Linear systems, least squares, singular value decomposition, eigenvalues. Communication routines targeting linear algebra operations. Level 1/2/3 Communication layer (message passing). http://acts.nersc.gov/scalapack

  15. PETSc PDE Application Codes ODE Integrators Visualization Nonlinear Solvers, Unconstrained Minimization Interface Linear Solvers Preconditioners + Krylov Methods Object-Oriented Matrices, Vectors, Indices Grid Management Profiling Interface Computation and Communication Kernels MPI, MPI-IO, BLAS, LAPACK PETSc Portable, Extensible Toolkit for Scientific Computation

  16. Observation “Explicit message passing will remain the dominant programming model for the foreseeable future because of the huge investment in application codes.” -Jim Tomkis, Bob Balance, and Sue Kelly, ASC PI Meeing, Nevada, Feb 2007

  17. Common Application Platform Basic Architecture Building Blocks Conclusions

  18. Basic Architecture Browser SURAgrid Portal Command-Line (GSISSH, etc.) SiteA MetaScheduler (MS) A B Site1 Site3 Site2

  19. Building Blocks MPICH-G2

  20. Conclusions • Powershift ! • Onus is now on System Administrators • Load Balancing • Minimize communication costs • Limits: ScaLAPACK (Latency<500 ms) • Dynamic Redistribution of Work • Heterogeneous Environment • Issues with floating-point operations

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