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Cactus 4.0

Cactus 4.0. Cactus Computational Toolkit and Distributed Computing. Solving Einstein’s Equations Impact on computation Large collaborations essential and difficult! Code becomes the collaborating tool. Cactus, a new community code for 3D GR-Astrophysics

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Cactus 4.0

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  1. Cactus 4.0

  2. Cactus Computational Toolkit and Distributed Computing • Solving Einstein’s Equations • Impact on computation • Large collaborations essential and difficult! • Code becomes the collaborating tool. • Cactus, a new community code for 3D GR-Astrophysics • Toolkit for many PDE systems • Suite of solvers for Einstein system • Metacomputing for the general user • Distributed computing experiments with Cactus and Globus Gabrielle Allen, Ed Seidel Albert-Einstein-Institut MPI-Gravitationsphysik

  3. Einstein’s Equations and Gravitational Waves s(t) h = ds/s ~ 10-22 ! Colliding BH’s and NS’s... • Einstein’s General Relativity • Fundamental theory of Physics (Gravity) • Black holes, neutron stars, gravitational waves, ... • Among most complex equations of physics • Dozens of coupled, nonlinear hyperbolic-elliptic equations with 1000’s of terms • New field: Gravitational Wave Astronomy • Will yield new information about the Universe • What are gravitational waves? “Ripples in the curvature of spacetime” • A last major test of Einstein’s theory: do they exist? • Eddington: “Gravitational waves propagate at the speed of thought” • 1993 Nobel Prize Committee: Hulse-Taylor Pulsar (indirect evidence)

  4. Detecting Gravitational Gravitational Waves • LIGO, VIRGO (Pisa), GEO600,…$1 Billion Worldwide • We need results from numerical relativity to: • Detect them…pattern matching against numerical templates to enhance signal/noise ratio • Understand them…just what are the waves telling us? Hanford Washington Site 4km

  5. Teraflop computation, AMR, elliptic-hyperbolic, ??? Merger Waveform Must Be Found Numerically

  6. Axisymmetric Black Hole Simulations: Cray C90 Collision of two Black Holes (“Misner Data”) Evolution of Highly Distorted Black Hole

  7. Computational Needs for 3D Numerical Relativity • Finite Difference Codes ~ 104 Flops/zone/time step ~ 100 3D arrays • Currently use 2503 ~ 15 GBytes ~ 15 TFlops/time step • Need 10003 zones ~1000 GBytes ~1000 TFlops/time step • Need TFlop, TByte machine • Need Parallel AMR, I/O t=100 t=0 • Initial Data: 4 couple nonlinear elliptics • Time step update • explicit hyperbolic update • also solve elliptics

  8. Mix of Varied Technologies and Expertise! • Scientific/Engineering: • formulation of equations, equation of state, astrophysics, hydrodynamics ... • Numerical Algorithms: • Finite differences? Finite elements? Structured meshes? • Hyperbolic equations: explicit vs implicit, shock treatments, dozens of methods (and presently nothing is fully satisfactory!) • Elliptic equations: multigrid, Krylov subspace, spectral, preconditioners (elliptics currently require most of the time…) • Mesh Refinement? • Computer Science: • Parallelism (HPF, MPI, PVM, ???) • Architecture Efficiency (MPP, DSM, Vector, NOW, ???) • I/O Bottlenecks (generate gigabytes per simulation, checkpointing…) • Visualization of all that comes out!

  9. Clearly need huge teams, with huge expertise base to attack such problems… • … in fact need collections of communities • But how can they work together effectively? • Need a code environment that encourages this…

  10. NSF Black Hole Grand Challenge Alliance • University of Texas (Matzner, Browne) • NCSA/Illinois/AEI (Seidel, Saylor, Smarr, Shapiro, Saied) • North Carolina (Evans, York) • Syracuse (G. Fox) • Cornell (Teukolsky) • Pittsburgh (Winicour) • Penn State (Laguna, Finn) Develop Code To Solve Gmn = 0

  11. NASA Neutron Star Grand Challenge • NCSA/Illinois/AEI (Saylor, Seidel, Swesty, Norman) • Argonne (Foster) • Washington U (Suen) • Livermore (Ashby) • Stony Brook (Lattimer) “A Multipurpose Scalable Code for Relativistic Astrophysics” Develop Code To Solve Gmn = 8pTmn

  12. What we learn from Grand Challenges • Successful, but also problematic… • No existing infrastructure to support collaborative HPC • Many scientists are Fortran programmers, and NOT computer scientists • Many sociological issues of large collaborations and different cultures • Many language barriers … … Applied mathematicians, computational scientists, physicists have very different concepts and vocabularies… • Code fragments, styles, routines often clash • Successfully merged code (after years) often impossible to transplant into more modern infrastructure (e.g., add AMR or switch to MPI…) • Many serious problems … this is what the Cactus Code seeks to address

  13. What Is Cactus? • Cactus was developed as a general, computational framework for solving PDEs (originally in numerical relativity and astrophysics) • Modular … for easy development, maintenance and collaborations. Users supply “thorns” which plug-into compact core “flesh” • Configurable … thorns register parameter, variable and scheduling information with “runtime function registry” (RFR). Object-orientated inspired features • Scientist friendly … thorns written in F77, F90, C, C++ • Accessible parallelism … driver layer (thorn) is hidden from physics thorns by a fixed flesh interface

  14. What Is Cactus? • Standard interfaces … interpolation, reduction, IO, coordinates. Actual routines supplied by thorns • Portable … Cray T3E, Origin, NT/Win9*, Linux, O2, Dec Alpha, Exemplar, SP2 • Free and open community code … distributed under the GNU GPL. Uses as much free software as possible • Up-to-date … new computational developments and/or thorns immediately available to users (optimisations, AMR, Globus, IO) • Collaborative … thorn structure makes it possible for large number of people to use and development toolkits … the code becomes the collaborating tool • New version … Cactus beta-4.0 released 30th August

  15. Core Thorn Arrangements Provide Tools • Parallel drivers (presently MPI-based) • (Mesh refinement schemes: Nested Boxes, DAGH, HLL) • Parallel I/O for Output, Filereading, Checkpointing (HDF5, FlexIO, Panda, etc…) • Elliptic solvers (Petsc, Multigrid, SOR, etc…) • Interpolators • Visualization Tools (IsoSurfacer) • Coordinates and boundary conditions • Many relativity thorns • Groups develop their own thorn arrangements to add to these

  16. Cactus 4.0 Boundary CartGrid3D WaveToyF77 WaveToyF90 PUGH FLESH (Parameters, Variables, Scheduling) GrACE IOFlexIO IOHDF5

  17. Current Status • It works: many people, with different backgrounds, different personalities, on different continents, working together effectively on problems of common interest. • Dozens of physics/astrophysics and computational modules developed and shared by “seed” community • Connected modules work together, largely without collisions • Test suites used to ensure integrity of both code and physics • How to get it … • Workshop 27 Sept - 1 Oct NCSA http://www.ncsa.uiuc.edu/SCD/Training/ Movie from Werner Benger, ZIB

  18. Near Perfect Scaling • Excellent scaling on many architectures • Origin up to 128 processors • T3E up to 1024 • NCSA NT cluster up to 128 processors • Achieved 142 Gflops/s on 1024 node T3E-1200 (benchmarked for NASA NS Grand Challenge)

  19. Many Developers: Physics & Computational Science DAGH/AMR (UTexas) AEI NCSA FlexIO ZIB Wash. U HDF5 NASA SGI Valencia Petsc (Argonne) Globus (Foster) Panda I/O (UIUC CS)

  20. Metacomputing: harnessing power when and where it is needed • Easy access to available resources • Find Resources for interactive use: Garching? ZIB? NCSA? SDSC? • Do I have an account there? What’s the password? • How do get executable there? • Where to store data? • How to launch simulation. What are local queue structure/OS idiosyncracies?

  21. Metacomputing: harnessing power when and where it is needed • Access to more resources • Einstein equations require extreme memory, speed • Largest supercomputers too small! • Networks very fast! • DFN gigabit testbed: 622 Mbits Potsdam-Berlin-Garching, connect multiple supercomputers • Gigabit networking to US possible • Connect workstations to make supercomputer

  22. Metacomputing: harnessing power when and where it is needed • Acquire resources dynamically during simulation! • Need more resolution in one area • Interactive visualization, monitoring and steering from anywhere • Watch simulation as it progresses … live visualisation • Limited bandwidth: compute vis. online with simulation • High bandwidth: ship data to be visualised locally • Interactive Steering • Are parameters screwed up? Very complex? • Is memory running low? AMR! What to do? Refine selectively or acquire additional resources via Globus? Delete unnecessary grids?

  23. Metacomputing: harnessing power when and where it is needed • Call up an expert colleague … let her watch it too • Sharing data space • Remote collaboration tools • Visualization server: all privileged users can login and check status/adjust if necessary

  24. Globus: Can provide many such services for Cactus • Information (Metacomputing Directory Service: MDS) • Uniform access to structure/state information: Where can I run Cactus today? • Scheduling (Globus Resource Access Manager: GRAM) • Low-level scheduler API: How do I schedule Cactus to run at NCSA? • Communications (Nexus) • Multimethod communication + QoS management: How do I connect Garching and ZIB together for a big run? • Security (Globus Security Infrastructure) • Single sign-on, key management: How do I get authority at SDSC for Cactus?

  25. Globus: Can provide many such services for Cactus • Health and status (Heartbeat monitor): Is my Cactus run dead? • Remote file access (Global Access to Secondary Storage: GASS): How do I manage my output, and get executable to Argonne?

  26. Colliding Black Holes and MetaComputing: German Project supported by DFN-Verein • Solving Einstein’s Equations • Developing Techniques to Exploit High Speed Networks • Remote Visualization • Distributed Computing Across OC-12 Networks between AEI (Potsdam), Konrad-Zuse-Institut (Berlin), and RZG (Garching-bei-München) AEI

  27. Distributing Spacetime: SC’97 Intercontinental Metacomputing at AEI/Argonne/Garching/NCSA Immersadesk 512 Node T3E

  28. Metacomputing the Einstein Equations:Connecting T3E’s in Berlin, Garching, San Diego

  29. Collaborators • A distributed astrophysical simulation involving the following institutions: • Albert Einstein Institute (Potsdam, Germany) • Washington University St. Louis, MO. • Argonne National Laboratory (Chicago, IL) • NLANR Distributed Applications Team (Champaign, IL) • The following supercomputer centers: • San Diego Supercomputer Center (268 proc. T3E) • Konrad-Zuse-Zentrum in Berlin (232 proc. T3E) • Max-Planck-Institute in Garching (768 proc. T3E)

  30. The Grand Plan • Distribute simulation across 128 PE’s of SDSC T3E and 128 PE’s of Konrad-Zuse-Zentrum T3E in Berlin, using Globus • Visualize isosurface data in real-time on Immersadesk in Orlando • Transatlantic bandwidth from an OC-3 ATM network San Diego Berlin

  31. SC98 Neutron Star Collision Movie from Werner Benger, ZIB

  32. Cactus scaling across PE’s(Jason Novotny, NLANR)

  33. Analysis of metacomputing experiments • It works! (That’s the main thing we wanted at SC98…) • Cactus not optimized for metacomputing: messages too small, lower MPI bandwidth, could be better: • ANL-NCSA • Measured bandwidth 17Kbits/sec (small) --- 25Mbits/sec (large) • Latency 4ms • Munich-Berlin • Measured bandwidth 1.5Kbits/sec (small) --- 4.2Mbits/sec (large) • Latency 42.5ms • Within single machine: Order of magnitude better • Bottom Line: • Expect to be able to improve performance significantly • Can run much larger jobs on multiple machines • Start using Globus routinely for job submission

  34. The Dream: not far away... Physics Module 1 BH Initial Data Cactus/Einstein solver MPI, MG, AMR, DAGH, Viz, I/O, ... Budding Einstein in Berlin... Globus Resource Manager Mass storage Ultra 3000: Whatever-Wherever Garching T3E NCSA Origin 2000 array

  35. Cactus 4.0 Credits • Toni Arbona • Carles Bona • Steve Brandt • Bernd Bruegmann • Thomas Dramlitsch • Ed Evans • Carsten Gundlach • Gerd Lanferman • Lars Nerger • Mark Miller • Hisaaki Shinkai • Ryoji Takahashi • Malcolm Tobias • Vision and Motivation • Bernard Schutz • Ed Seidel "the Evangelist" • Wai-Mo Suen • Cactus flesh and design • Gabrielle Allen • Tom Goodale • Joan Massó • Paul Walker • Computational toolkit • Flesh authors • Gerd Lanferman • Thomas Radke • John Shalf • Development toolkit • Bernd Bruegmann • Manish Parashar • Many others • Relativity and astrophysics • Flesh authors • Miguel Alcubierre

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