1 Cactus in a nutshell... n Cactus facilitates parallel code design, it enables platform independent computations and encourages collaborative code development.

Slides:



Advertisements
Similar presentations
National Institute of Advanced Industrial Science and Technology Ninf-G - Core GridRPC Infrastructure Software OGF19 Yoshio Tanaka (AIST) On behalf.
Advertisements

INTRODUCTION TO SIMULATION WITH OMNET++ José Daniel García Sánchez ARCOS Group – University Carlos III of Madrid.
Beowulf Supercomputer System Lee, Jung won CS843.
ProActive Task Manager Component for SEGL Parameter Sweeping Natalia Currle-Linde and Wasseim Alzouabi High Performance Computing Center Stuttgart (HLRS),
Presented by Scalable Systems Software Project Al Geist Computer Science Research Group Computer Science and Mathematics Division Research supported by.
Cactus in GrADS (HFA) Ian Foster Dave Angulo, Matei Ripeanu, Michael Russell.
Problem-Solving Environments: The Next Level in Software Integration David W. Walker Cardiff University.
Supporting Efficient Execution in Heterogeneous Distributed Computing Environments with Cactus and Globus Gabrielle Allen, Thomas Dramlitsch, Ian Foster,
Cactus Code and Grid Programming Here at GGF1: Gabrielle Allen, Gerd Lanfermann, Thomas Radke, Ed Seidel Max Planck Institute for Gravitational Physics,
GridLab & Cactus Joni Kivi Maarit Lintunen. GridLab  A project funded by the European Commission  The project was started in January 2002  Software.
Software Issues Derived from Dr. Fawcett’s Slides Phil Pratt-Szeliga Fall 2009.
EUROPEAN UNION Polish Infrastructure for Supporting Computational Science in the European Research Space Cracow Grid Workshop’10 Kraków, October 11-13,
SUN HPC Consortium, Heidelberg 2004 Grid(Lab) Resource Management System (GRMS) and GridLab Services Krzysztof Kurowski Poznan Supercomputing and Networking.
Parallelization with the Matlab® Distributed Computing Server CBI cluster December 3, Matlab Parallelization with the Matlab Distributed.
STRATEGIES INVOLVED IN REMOTE COMPUTATION
SICSA student induction day, 2009Slide 1 Social Simulation Tutorial Session 6: Introduction to grids and cloud computing International Symposium on Grid.
Cornell Theory Center Aug CCTK The Cactus Computational Toolkit Werner Benger Max-PIanck-Institut für Gravitationsphysik (Albert-Einstein-Institute.
ICOM 5995: Performance Instrumentation and Visualization for High Performance Computer Systems Lecture 7 October 16, 2002 Nayda G. Santiago.
Tools and Utilities for parallel and serial codes in ENEA-GRID environment CRESCO Project: Salvatore Raia SubProject I.2 C.R. ENEA-Portici. 11/12/2007.
CLUSTER COMPUTING STIMI K.O. ROLL NO:53 MCA B-5. INTRODUCTION  A computer cluster is a group of tightly coupled computers that work together closely.
1b.1 Types of Parallel Computers Two principal approaches: Shared memory multiprocessor Distributed memory multicomputer ITCS 4/5145 Parallel Programming,
Grads Meeting - San Diego Feb 2000 The Cactus Code Gabrielle Allen Albert Einstein Institute Max Planck Institute for Gravitational Physics
Compiler BE Panel IDC HPC User Forum April 2009 Don Kretsch Director, Sun Developer Tools Sun Microsystems.
Cactus Project & Collaborative Working Gabrielle Allen Max Planck Institute for Gravitational Physics, (Albert Einstein Institute)
BLU-ICE and the Distributed Control System Constraints for Software Development Strategies Timothy M. McPhillips Stanford Synchrotron Radiation Laboratory.
Debugging and Profiling GMAO Models with Allinea’s DDT/MAP Georgios Britzolakis April 30, 2015.
Computer Fundamentals MSCH 233 Lecture 2. What is a Software? Its step by step instructions telling the computer how to process data, execute operations.
Applications for the Grid Here at GGF1: Gabrielle Allen, Thomas, Dramlitsch, Gerd Lanfermann, Thomas Radke, Ed Seidel Max Planck Institute for Gravitational.
N*Grid – Korean Grid Research Initiative Funded by Government (Ministry of Information and Communication) 5 Years from 2002 to million US$ Including.
The Globus Project: A Status Report Ian Foster Carl Kesselman
1 SIAC 2000 Program. 2 SIAC 2000 at a Glance AMLunchPMDinner SunCondor MonNOWHPCGlobusClusters TuePVMMPIClustersHPVM WedCondorHPVM.
Resource Brokering in the PROGRESS Project Juliusz Pukacki Grid Resource Management Workshop, October 2003.
Issues Autonomic operation (fault tolerance) Minimize interference to applications Hardware support for new operating systems Resource management (global.
Presented by An Overview of the Common Component Architecture (CCA) The CCA Forum and the Center for Technology for Advanced Scientific Component Software.
NIH Resource for Biomolecular Modeling and Bioinformatics Beckman Institute, UIUC NAMD Development Goals L.V. (Sanjay) Kale Professor.
NIH Resource for Biomolecular Modeling and Bioinformatics Beckman Institute, UIUC NAMD Development Goals L.V. (Sanjay) Kale Professor.
6/12/99 Java GrandeT. Haupt1 The Gateway System This project is a collaborative effort between Northeast Parallel Architectures Center (NPAC) Ohio Supercomputer.
The Cactus Code: A Problem Solving Environment for the Grid Gabrielle Allen, Gerd Lanfermann Max Planck Institute for Gravitational Physics.
Scalable Systems Software for Terascale Computer Centers Coordinator: Al Geist Participating Organizations ORNL ANL LBNL.
Cactus/TIKSL/KDI/Portal Synch Day. Agenda n Main Goals:  Overview of Cactus, TIKSL, KDI, and Portal efforts  present plans for each project  make sure.
GridLab WP-2 Cactus GAT (CGAT) Ed Seidel, AEI & LSU Co-chair, GGF Apps RG, Gridstart Apps TWG Gabrielle Allen, Robert Engel, Tom Goodale, *Thomas Radke.
NEES Cyberinfrastructure Center at the San Diego Supercomputer Center, UCSD George E. Brown, Jr. Network for Earthquake Engineering Simulation NEES TeraGrid.
Connections to Other Packages The Cactus Team Albert Einstein Institute
 Programming - the process of creating computer programs.
August 2003 At A Glance The IRC is a platform independent, extensible, and adaptive framework that provides robust, interactive, and distributed control.
Capacity and Capability Computing using Legion Anand Natrajan ( ) The Legion Project, University of Virginia (
2/22/2001Greenbook 2001/OASCR1 Greenbook/OASCR Activities Focus on technology to enable SCIENCE to be conducted, i.e. Software tools Software libraries.
Java – in context Main Features From Sun Microsystems ‘White Paper’
Conundrum Talk, LBL May 2000 The Cactus Code: A Framework for Parallel Computing Gabrielle Allen Albert Einstein Institute Max Planck Institute for Gravitational.
Lesson 1 1 LESSON 1 l Background information l Introduction to Java Introduction and a Taste of Java.
Albert-Einstein-Institut Exploring Distributed Computing Techniques with Ccactus and Globus Solving Einstein’s Equations, Black.
Dynamic Grid Computing: The Cactus Worm The Egrid Collaboration Represented by: Ed Seidel Albert Einstein Institute
PROGRESS: GEW'2003 Using Resources of Multiple Grids with the Grid Service Provider Michał Kosiedowski.
From Use Cases to Implementation 1. Structural and Behavioral Aspects of Collaborations  Two aspects of Collaborations Structural – specifies the static.
Cactus Workshop - NCSA Sep 27 - Oct Generic Cactus Workshop: Summary and Future Ed Seidel Albert Einstein Institute
Metacomputing Within the Cactus Framework What and why is Cactus? What has Cactus got to do with Globus? Gabrielle Allen, Thomas Radke, Ed Seidel. Albert-Einstein-Institut.
Ganga/Dirac Data Management meeting October 2003 Gennady Kuznetsov Production Manager Tools and Ganga (New Architecture)
From Use Cases to Implementation 1. Mapping Requirements Directly to Design and Code  For many, if not most, of our requirements it is relatively easy.
Towards a High Performance Extensible Grid Architecture Klaus Krauter Muthucumaru Maheswaran {krauter,
Cactus Project & Collaborative Working
Clouds , Grids and Clusters
The Cactus Team Albert Einstein Institute
Grid Computing AEI Numerical Relativity Group has access to high-end resources in over ten centers in Europe/USA They want: Bigger simulations, more simulations.
Exploring Distributed Computing Techniques with Ccactus and Globus
University of Technology
Dynamic Grid Computing: The Cactus Worm
Overview of big data tools
Java Programming Introduction
FEniCS = Finite Element - ni - Computational Software
From Use Cases to Implementation
Presentation transcript:

1 Cactus in a nutshell... n Cactus facilitates parallel code design, it enables platform independent computations and encourages collaborative code development between different groups. n Cactus was developed as a 3D parallel high-performance tool for Numerical Relativity which would allow easy development and maintenance especially for collaborations. n Modular structure: user code (a “thorn”) plugs into compact core code (“flesh”) through an extensible interface. Cactus allows a programmer to concentrate on his area of expertise. n User friendly: thorns can be written in C, C++ or Fortran 77/90, communication programming is optionally abstracted away from the user. n Cactus offers access to a range of computational capabilities as e.g. parallel I/O, checkpoiting, remote steering & visualization, performance analysis and provides easy access to many cutting edge software packages as Globus HDF5, PETSc. n Developed, supported and expanded by the Albert-Einstein-Institute in collaboration with many other institutes and universities worldwide, released under GNU Opensource license. Information & Download:

2 “Big mesh sizes” Collaboration technology needed! n A scientist’s view on a large scale computation problem: Initial Data Evolution Algorithms Analysis routines (Bettter be Fortran) “Easy job submission” “Large Data Output” “Parallel would be great” Scientist cannot be required to become experts in IT technology.

3 Collaboration technology needed! n An IT expert’s view on a large scale computation problem: Next Gen. Highspeed Comm. Layers High-performance parallel I/O Code instrumentation + steering Load scheduling Interactive Viz. Metacomputing “Programmers, use this!” IT experts cannot write the applications that make use of their technology

4 Large Scale Computations Require a mix of Technologies and Expertise n Scientific/Engineering Components The “physics” in the game n Numerical Algorithm Components Finite differences? Finite elements? Structured meshes? n Different Computational Components l Architectures and plattforms l Parallelism (MPI, PVM, OpenMP, ???) l parallel I/O, Data Management, Queueing Systems l Visualization of all that comes out! How can experts work together effectively? Need a code environment that encourages collaborative HPC.

5 Cactus “glue” Cactus „glue“ Initial Data Evolution Algorithms Elliptic Equation Solver AMR/FMR Parallelisation MPI/PVM/ OpenMP/Shmem (High Performance-) Input/Output Checkpointing Code Instrumentation / Bencharking Interactive Steering Interactiv Visualisation Cactus’ goal is to provide a modular framework that allows each technology to be of impact to other unrelated fields.

6 Cactus “glue” in more detail n Cactus “Flesh” (core) written in C n User “thorns” (modules) grouped in arrangements, can be written in F77, F90, C, C++, (Java) n Thorn -- Flesh interface fixed in 3 files written in CCL (Cactus Configuration Language): l interface.ccl: Grid Variables, Arrays, Scalars (integer, real, logical, complex) l param.ccl: Parameters and their allowed values l schedule.ccl: Scheduling of routines, dynamic memory allocation n Object orientated features (public, private, protected variables, inheritance) define scope of objects and ensure non-contaminating modularity. n Flesh provides standard interfaces for Parallelization, Interpolation, Reduction, I/O, etc. Underlying technology can be replaced invisibly to the user

7 How to use Cactus n Develop thorns, according to the interface rules l interface.ccl + schedule.ccl + param.ccl l Specify calling sequence of the routines for different problems and algorithms (schedule.ccl) For a given code: strip off parameter parsing / memory allocation / output n At compile time: l Specify which thorns are to be compiled into executable. l Redundancy allowed: Multiple thorns providing the same functionality. E.g. different Evolutions systems, IO methods. n At run time: l In the parameter file, turn on the thorns needed for your simulation.

8 Cactus architectures & environments Cactus applications developed on a standard workstation or laptop can be seamlesly run on a cluster or supercomputer. Supported architectures: n SGI Origin n Cray T3E n Compaq DEC Alpha n Linux (IA32/64,PPC,NOWs) n Windows NT n IBM SP2 n Hitachi n HP n SUN Ultra. Homogenous + heterogenous networks: “What is a supercomputer and what is not ? “ Computing in a resource continuum

9 Cactus, Egrid, KDI n The European Grid Forum (Egrid) aims at the cooperative use of the distributed computing resources that are accessible via wide area networks. n 18 participating organisations of the 1 st Egrid workshop in Poznan chose to install Cactus as a first testbed application.

10 HPC in Numerical Relativity n SC 97: “Distributed Spacetime”, Intercontinental Metacomputing at AEI / Argonne / Garching / NCSA (512 node T3E calculation with live visualization San Jose) n SC98: “Colliding Neutron Stars across the Atlantic”, Connecting T3E’s in Berlin, Garching, San Diego n SC99: Cactus used by several independent demos as underlying framework. n In Fall 99: