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Projects using Cactus. Gabrielle Allen gallen@cct.lsu.edu Cactus Retreat Baton Rouge, April 2004. Cactus Projects @ AEI/LSU. User Support Applications Research and Development Support for more numerical models (Saturday) Large scale computing Frameworks Visualization
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Projects using Cactus Gabrielle Allen gallen@cct.lsu.edu Cactus RetreatBaton Rouge, April 2004
Cactus Projects @ AEI/LSU • User Support • Applications • Research and Development • Support for more numerical models (Saturday) • Large scale computing • Frameworks • Visualization • Data models and formats • Grid computing
Community Development • Adaptive Mesh Refinement • PAGH (Wash U) • Carpet (Albert Einstein Institute) • Application Performance Modeling • University of Chicago • Data Formats and Visualization • Lawrence Berkeley Lab • Konrad Zuse Zentrum • Albert Einstein Institute • Optimization and Performance • NCSA, Intel, Cray, Lawrence Berkeley Lab, Absoft • User GUIs • Wash U
Interoperability • Pending proposal to NSF ITR program • “Hypercode: Interoperable Infrastructure Initiative” • Addressing interoperability for general computational infrastructures, • Cactus, Chombo, Paramesh and CCA-based frameworks • Focused around applications: • Numerical Relativity • Computational Astrophysics • Coastal Modeling • Climate Modeling • Cosmology • Computational Fluid Dynamics
Interoperability • Develop common mechanisms and abstractions to enable different simulation codes to use modules and data interchangeably • Partners: • LSU • LBL (John Shalf, Phil Colella, Julian Borill) • U. Maryland (Kevin Olsen, Joan Centrella) • U. Indiana (Denis Gannon) • NCSA (Greg Daues)
Interoperability • Main developments for Cactus: • Incorporate other AMR drivers into Cactus • Chombo, Paramesh • Incorporate other elliptic solvers into Cactus • Develop a community toolkit for CFD • Add new features to Cactus • Adaptivity • Dynamic component loading • Develop common data model • New visualization tools available
Visualization • Ongoing visualization projects at AEI, LSU, LBL with Cactus • Pending DST-NSF proposal with the computer science department and C-DAC to build visualization infrastructure to allow data to be analyzed and visualized on the fly • Additions to Cactus I/O infrastructure • Thorns for visualization • Web-based visualization tools
Large Scale Computing • NSF Software Technologies for High End Computing • (being written) • Incorporate fault tolerant MPI in Cactus driver layer • University of Tennessee • Develop HTTPD thorn into an interactive, real time parallel debugger • Detect and exploit memory and network connection hierarchy from processor cache, through node layout on clusters of SMPs, to cluster interconnections on the Grid • Performance monitoring and adaption using e.g. PAPI library
Grid Computing “resource sharing and coordinated problem solving in dynamic, multi-institutional virtual organizations” … infrastructure enabling the integrated, collaborative use of high-end computers, networks, databases, scientific instruments owned and managed by multiple organizations … … applications often involve large amounts of data and/or computing, secure resource sharing across organizational boundaries, not easily handled by today’s Internet and Web infrastructures …
HTTPD Thorn which allows simulation to any to act as its own web server Connect to simulation from any browseranywhere … collaborate Monitor run: parameters, basic visualization, ... Change steerable parameters Running example at www.CactusCode.org Wireless remote viz, monitoring and steering Remote Monitoring/Steering:
User Portal (ASC and GridSphere) • Collaboration focal point for a virtual organization • Interact, share data • Start jobs on remote resources • Move/browse files • Track and monitor announced jobs • Access to new Grid technologies • www.ascportal.org • www.gridsphere.org
Notification (Announce) Running Appli cations “TestBed” SMS Server Portal Server Mail Server
OpenDX, Amira, … HDF5 GridFTP VFD Stream VFD Remote Data and Visualization (GriKSL) Visualization Tools Hyperslabbing, Downsampling IOStreamedHDF5 GridFTP Remote Data Server Simulation
GigE:100MB/sec 17 4 12 5 SDSC IBM SP 1024 procs 5x12x17 =1020 Dynamic Adaptive Distributed Computation 2 2 OC-12 line (But only 2.5MB/sec) 12 5 NCSA Origin Array 256+128+128 5x12x(4+2+2) =480 These experiments: • Einstein Equations (but could be any Cactus application) Achieved: • First runs: 15% scaling • With new techniques: 70-85% scaling, ~ 250GF Dynamic Adaptation: Number of ghostzones, compression, … “Gordon Bell Prize” (Supercomputing 2001, Denver)
New Grid Scenarios • Intelligent Parameter Surveys, Monte Carlo • Dynamic Migration: faster/cheaper/bigger machine • Multiple Universe: create clone to investigate steered parameter • Automatic Component Loading (Needs of process change) • Automatic Convergence Testing • Look Ahead • Spawn Independent/Asynchronous Tasks • Routine Profiling: best machine/queue, parameters • Dynamic Load Balancing: inhomogeneous loads, multiple grids
GridLab • Cactus experiments with grid computing on the E-Grid • Cactus Worm: thorns which allowed simulations to migrate themselves from machine to machine • Spawning: sending (asynchronous) calculations in analysis thorns to different machines • We wrote the GridLab proposal to be able to do these, and other scenarios, in a better way
GridLab Project • http://www.gridlab.org • EU Funded ($5M) by 5th Framework • January 2002-December 2004): • Many partners in Europe and US • PSNC (Poland), AEI & ZIB (Germany), VU (Netherlands), MASARYK (Czech), SZTAKI (Hungary), ISUFI (Italy), Cardiff (UK), NTUA (Greece), Chicago, ISI & Wisconsin (US), Sun/Compaq • LSU now a collaborating partner
GridLab • Developing an easy-to-use, flexible, generic and modular Grid Application Toolkit (GAT), enabling applications to make innovative use of global computing resources • Focused on two principles: • co-development of infrastructure with real applications and user communities (Badly needed in grid computing!!) • dynamic use of grids, with self-aware simulations adapting to their changing environment.
GridLab • 12 Work Packages covering: Grid Portals Mobile Users Different Grid Services Applications (Development) Test Bed Grid Application Toolkit (GAT)
Grid Application Toolkit Need a layer between applications and grid infrastructure: • Higher level than existing grid APIs, hide complexity, abstract grid functionality through application oriented APIs • Insulate against rapid evolution of grid infrastructure and state of grid deployment • Choose between different grid infrastructures • Make it possible for application developers to use and develop for the grid independent of the state of deployment of the grid infrastructure
Application “Is there a better resource I could be using?” SOAP WSDL Corba OGSA Other Monitoring Profiling Information Logging Security Notification Resource Management Application Manager Migration Data Management GLOBUS Other Grid Infrastructure?
Application “Is there a better resource I could be using?” GAT_FindResource( ) The Grid
The Same Application … Laptop Super Computer The Grid Application Application Application GAT GAT GAT Firewall issues! No network!
GAT: Grid Application Toolkit • Standard API and Toolkit for developing portable Grid applications independently of the underlying Grid infrastructure and available services • Implements the GAT-API • Used by applications (different languages) • GAT Adaptors • Connect to capabilities/services • GAT Engine • Provides the function bindings for the GAT-API • http://www.gridlab.org/software/GAT
Cactus/GAT Integration Cactus Flesh Grid Scenario Thorn Grid Scenario Thorn Thorn Thorn GAT Library CGAT Thorn Thorn Thorn Thorn Cactus GAT wrappers Additional functionality Build system Physics and Computational Infrastructure Modules GridLab Service GridLab Service
Task Farming on the Grid TFM implemented in Cactus TFM GAT used for starting remote TFMs TFM TFM Designed for the Grid TFM TFM Tasks can be anything
Grid-Black Holes • Task farm small Cactus black hole simulations across testbed • Parameter survey: black hole corotation parameter • Results steer a large production black hole simulation
SDSC S Brill Wave RZG SDSC LRZ S1 Calculate/Output Invariants S2 Archive data P1 Found a horizon, try out excision P2 Calculate/Output Grav. Waves Look for horizon S2 S1 Archive to LIGO public database Find best resources P2 P1 NCSA Dynamic Grid Computing Add more resources Queue time over, find new machine Free CPUs!! Clone job with steered parameter Physicist has new idea !