Problem-Solving Environments: The Next Level in Software Integration David W. Walker Cardiff University.

Slides:



Advertisements
Similar presentations
Building a CFD Grid Over ThaiGrid Infrastructure Putchong Uthayopas, Ph.D Department of Computer Engineering, Faculty of Engineering, Kasetsart University,
Advertisements

Prof. Natalia Kussul, PhD. Andrey Shelestov, Lobunets A., Korbakov M., Kravchenko A.
1 From Grids to Service-Oriented Knowledge Utilities research challenges Thierry Priol.
A Workflow Engine with Multi-Level Parallelism Supports Qifeng Huang and Yan Huang School of Computer Science Cardiff University
Kensington Oracle Edition: Open Discovery Workflow Meets Oracle 10g Professor Yike Guo.
C3.ca in Atlantic Canada Virendra Bhavsar Director, Advanced Computational Research Laboratory (ACRL) Faculty of Computer Science University of New Brunswick.
ASCR Data Science Centers Infrastructure Demonstration S. Canon, N. Desai, M. Ernst, K. Kleese-Van Dam, G. Shipman, B. Tierney.
Towards a Virtual European Supercomputing Infrastructure Vision & issues Sanzio Bassini
1 OBJECTIVES To generate a web-based system enables to assemble model configurations. to submit these configurations on different.
High Performance Computing Course Notes Grid Computing.
ProActive Task Manager Component for SEGL Parameter Sweeping Natalia Currle-Linde and Wasseim Alzouabi High Performance Computing Center Stuttgart (HLRS),
Chapter Chapter Goals Describe the layers of a computer system Describe the concept of abstraction and its relationship to computing Describe.
Office of Science U.S. Department of Energy Grids and Portals at NERSC Presented by Steve Chan.
1 Dr. Frederica Darema Senior Science and Technology Advisor NSF Future Parallel Computing Systems – what to remember from the past RAMP Workshop FCRC.
Grids and Grid Technologies for Wide-Area Distributed Computing Mark Baker, Rajkumar Buyya and Domenico Laforenza.
UNICORE UNiform Interface to COmputing REsources Olga Alexandrova, TITE 3 Daniela Grudinschi, TITE 3.
UT-BATTELLE High Performance Computing: Past Highlights and Future Trends David W.Walker Computer Science and Mathematics Division Oak Ridge National.
Jun Peng Stanford University – Department of Civil and Environmental Engineering Nov 17, 2000 DISSERTATION PROPOSAL A Software Framework for Collaborative.
Advanced Data Mining and Integration Research for Europe ADMIRE – Framework 7 ICT ADMIRE Overview European Commission 7 th.
Web-based Portal for Discovery, Retrieval and Visualization of Earth Science Datasets in Grid Environment Zhenping (Jane) Liu.
Information Technology for Ocean Observations and Climate Research TYKKI Workshop, December 9-11, 1998, Tokyo, Japan Nancy N. Soreide NOAA Pacific Marine.
EUROPEAN UNION Polish Infrastructure for Supporting Computational Science in the European Research Space Cracow Grid Workshop’10 Kraków, October 11-13,
Apache Airavata GSOC Knowledge and Expertise Computational Resources Scientific Instruments Algorithms and Models Archived Data and Metadata Advanced.
OpenAlea An OpenSource platform for plant modeling C. Pradal, S. Dufour-Kowalski, F. Boudon, C. Fournier, C. Godin.
INFSO-SSA International Collaboration to Extend and Advance Grid Education ICEAGE Forum Meeting at EGEE Conference, Geneva Malcolm Atkinson & David.
DORII Joint Research Activities DORII Joint Research Activities Status and Progress 4 th All-Hands-Meeting (AHM) Alexey Cheptsov on.
Holding slide prior to starting show. A Grid-based Problem Solving Environment for GECEM Maria Lin and David Walker Cardiff University Yu Chen and Jason.
ICOM 5995: Performance Instrumentation and Visualization for High Performance Computer Systems Lecture 7 October 16, 2002 Nayda G. Santiago.
DISTRIBUTED COMPUTING
© 2007 Pearson Addison-Wesley. All rights reserved 0-1 Spring(2007) Instructor: Qiong Cheng © 2007 Pearson Addison-Wesley. All rights reserved.
Forschungszentrum Jülich UNICORE and EUROGRID: Grid Computing in EUROPE Dietmar Erwin Forschungszentrum Jülich GmbH TERENA Networking Conference 2001 Antalya,
Chapter 1 The Big Picture.
MathCore Engineering AB Experts in Modeling & Simulation WTC.
1 Cactus in a nutshell... n Cactus facilitates parallel code design, it enables platform independent computations and encourages collaborative code development.
ITPA/IMAGE 7-10 May 2007 Software and Hardware Infrastructure for the ITM B.Guillerminet, on behalf of the ITM & ISIP teams (P Strand, F Imbeaux, G Huysmans,
The Globus Project: A Status Report Ian Foster Carl Kesselman
Issues in (Financial) High Performance Computing John Darlington Director Imperial College Internet Centre Fast Financial Algorithms and Computing 4th.
Center for Component Technology for Terascale Simulation Software CCA is about: Enhancing Programmer Productivity without sacrificing performance. Supporting.
Service - Oriented Middleware for Distributed Data Mining on the Grid ,劉妘鑏 Antonio C., Domenico T., and Paolo T. Journal of Parallel and Distributed.
Presented by An Overview of the Common Component Architecture (CCA) The CCA Forum and the Center for Technology for Advanced Scientific Component Software.
UT-BATTELLE A Collaborative Code Development Environment for Computational Electromagnetics David W. Walker, Oak Ridge National Lab Omer Rana, Matthew.
6/12/99 Java GrandeT. Haupt1 The Gateway System This project is a collaborative effort between Northeast Parallel Architectures Center (NPAC) Ohio Supercomputer.
Futures Lab: Biology Greenhouse gasses. Carbon-neutral fuels. Cleaning Waste Sites. All of these problems have possible solutions originating in the biology.
Holding slide prior to starting show. A Portlet Interface for Computational Electromagnetics on the Grid Maria Lin and David Walker Cardiff University.
NA-MIC National Alliance for Medical Image Computing UCSD: Engineering Core 2 Portal and Grid Infrastructure.
The Grid the united computing power Jian He Amit Karnik.
GRID ARCHITECTURE Chintan O.Patel. CS 551 Fall 2002 Workshop 1 Software Architectures 2 What is Grid ? "...a flexible, secure, coordinated resource- sharing.
Grid programming with components: an advanced COMPonent platform for an effective invisible grid © 2006 GridCOMP Grids Programming with components. An.
GVis: Grid-enabled Interactive Visualization State Key Laboratory. of CAD&CG Zhejiang University, Hangzhou
GRID Overview Internet2 Member Meeting Spring 2003 Sandra Redman Information Technology and Systems Center and Information Technology Research Center National.
ISERVOGrid Architecture Working Group Brisbane Australia June Geoffrey Fox Community Grids Lab Indiana University
Terena conference, June 2004, Rhodes, Greece Norbert Meyer The effective integration of scientific instruments in the Grid.
Grid Enabled Neurosurgical Imaging Using Simulation
1 HPC Middleware on GRID … as a material for discussion of WG5 GeoFEM/RIST August 2nd, 2001, ACES/GEM at MHPCC Kihei, Maui, Hawaii.
August 3, March, The AC3 GRID An investment in the future of Atlantic Canadian R&D Infrastructure Dr. Virendra C. Bhavsar UNB, Fredericton.
National Computational Science Alliance Visualization and GIS at NCSA (Polly Baker, Group
RealityGrid Peter Coveney 1 and John Brooke 2 1. Centre for Computational Science, Department of Chemistry, Queen Mary, University of London 2. Manchester.
Connections to Other Packages The Cactus Team Albert Einstein Institute
Visualization in Problem Solving Environments Amit Goel Department of Computer Science Virginia Tech June 14, 1999.
7. Grid Computing Systems and Resource Management
GRID ANATOMY Advanced Computing Concepts – Dr. Emmanuel Pilli.
Holding slide prior to starting show. Lessons Learned from the GECEM Portal David Walker Cardiff University
INFSO-RI JRA2 Test Management Tools Eva Takacs (4D SOFT) ETICS 2 Final Review Brussels - 11 May 2010.
ETICS An Environment for Distributed Software Development in Aerospace Applications SpaceTransfer09 Hannover Messe, April 2009.
Page : 1 SC2004 Pittsburgh, November 12, 2004 DEISA : integrating HPC infrastructures in Europe DEISA : integrating HPC infrastructures in Europe Victor.
Holding slide prior to starting show. GECEM: Grid-Enabled Computational Electromagnetics David W. Walker School of Computer Science Cardiff University.
Grid Enabled Optimisation and Design Search for Engineering (GEODISE) Prof Simon Cox Southampton University
Clouds , Grids and Clusters
University of Technology
Polly Baker Division Director: Data, Mining, and Visualization
Presentation transcript:

Problem-Solving Environments: The Next Level in Software Integration David W. Walker Cardiff University

31/8/99 David W. Walker, Cardiff University 2 Objectives of this talk n To review the purpose and scope of PSEs n To discuss the requirements for constructing PSEs n To identify the major technologies that will serve as the infrastructure of PSEs n To review the PSEs currently in development and in use

31/8/99 David W. Walker, Cardiff University 3 Why PSEs? n Need: enhanced scientific insight; reduced development costs; improved product quality and industrial efficiency. n Need: transparent means of integrating distributed computers, instruments, sensors, and people. n Need: improved software productivity to extract maximum benefit from advances in computers, networks, and algorithms.

31/8/99 David W. Walker, Cardiff University 4 Why Now? n Confluence of complementary technologies. n Faster networks and communications. n Network software technologies such as CORBA, Java, and XML. n “Big Science” is inherently distributed and collaborative, and needs to migrate to WAN environments to progress.

31/8/99 David W. Walker, Cardiff University 5 What’s the Problem? n High-level, problem-specification languages, often coupled with expert system. For example, PDE solvers, numerical integration, etc. n Problem composition in form of dataflow graph using a GUI. Typically used in modelling and simulation of physical systems.

31/8/99 David W. Walker, Cardiff University 6 PSE Requirements n Expert assistance in problem specification and input. n Transparent access to distributed heterogeneous resources. n Interactivity and computational steering. n Advanced/immersive visualisation. n Integration with other knowledge repositories and databases.

31/8/99 David W. Walker, Cardiff University 7 Technologies for PSEs Hardware: n Increasingly powerful computers n Increasingly fast networks - gigabit ethernet, vBNS, etc. n Immersive visualisation platforms - CAVEs, ImmersaDesks, etc.

31/8/99 David W. Walker, Cardiff University 8 Technologies for PSEs Software: n CORBA for transparent interaction between distributed resources. n Java for platform-independent programming. n XML interface specification. n MPI for message-passing in SPMD codes.

31/8/99 David W. Walker, Cardiff University 9 An Example PSE Architecture Main PSE sub-systems are: n Visual Program Composition Environment (VPCE) for graphically composing applications. n Intelligent Resource Management System (IRMS) for scheduling applications on distributed resources.

31/8/99 David W. Walker, Cardiff University 10 VPCE Overview n GUI is used to build an application from software components - either a java or CORBA object with its interface specified in XML. n Each component may have a performance model and help file. n An annotated dataflow graph is produced that is passed to the IRMS.

31/8/99 David W. Walker, Cardiff University 11 IRMS Overview n IRMS locates software and hardware resources through information servers. n IRMS then schedules components on appropriate resources based on performance models and database of experience from previous runs. Genetic and neural network algorithms may be used.

31/8/99 David W. Walker, Cardiff University 12 The PSE Research Community n European Research Conference on PSEs took place June 1999 in Spain. Next one in summer n EuroTools SIG on PSEs. n Cardiff PSE project web site.

31/8/99 David W. Walker, Cardiff University 13 US Software Infrastructure n Globus: provides core services for grid- enabled computing. n Legion: an object-based metacomputing project. The Grid is a computational and network infrastructure providing pervasive, uniform, and reliable access to distributed resources.

31/8/99 David W. Walker, Cardiff University 14 European Software Infrastructure n UNICORE: Uniform access to Computing Resources. Aimed at providing uniform, secure, batch access to distributed resources. n POLDER: a more ambitious metacomputing project.

31/8/99 David W. Walker, Cardiff University 15 European Software Infrastructure n CODINE: resource management system targeted at optimal use of all software and hardware resources in a heterogeneous networked environment. n CCS: Computing Centre Software - resource management for networked high-performance computers.

31/8/99 David W. Walker, Cardiff University 16 European Software Infrastructure n GRD: Global Resource Director for distributed environments featuring policy management and dynamic scheduling. n NWIRE: Netwide resources - management system for WAN-based resources.

31/8/99 David W. Walker, Cardiff University 17 COVISE Visualisation Environment n The Collaborative Visualisation and Simulation Environment is a distributed software environment that seamlessly integrates simulations, post-processing, and visualisation. n COVISE supports collaborative working, and is available commercially.

31/8/99 David W. Walker, Cardiff University 18 Ctadel and PDE Problems n Code-generation tool for applications based on differential equations using high-level language specifications is an environment for the automatic generation of efficient Fortran or HPF programs for PDE-based problems. n Used in HIRLAM numerical weather forecast system.

31/8/99 David W. Walker, Cardiff University 19 An Environment for Cellular Automata n CAMEL n CAMEL is a CA environment designed for message-passing parallel computers. It hides parallelism issues from a user. CARPET User specifies only the transition function of a single cell of the system with CARPET, a high-level cellular language.

31/8/99 David W. Walker, Cardiff University 20 A PSE for Numerical General Relativity n CACTUS is a collaborative software environment for composing applications for the solution of general relativity problems. n Has been used in distributed computing experiments using Globus. n Interactive visualisation important.

31/8/99 David W. Walker, Cardiff University 21 JACO3: Industrial Design PSE n Java and CORBA based collaborative environment for coupled simulations. n A CORBA based high performance distributed computing environment for coupling simulation codes. n Optimal design of complex and expensive products like airplanes, satellites, or cars.

31/8/99 David W. Walker, Cardiff University 22 A PSE for Stochastic Analysis n Promenvir: Probabilistic mechanical design environment - a metacomputing tool for stochastic analysis. n It can automatically generate a series of stochastic computational experiments, and run them on the available resources n It has been used for optimal design problems in the automobile industry.

31/8/99 David W. Walker, Cardiff University 23 PSE for Engineering Simulations n JULIUS: Joint Industrial Interface for End-User Simulations. n Integrated HPC environment for multi- disciplinary engineering simulations. n Aimed at reducing design time for industrial products. n End-users are engineers.

31/8/99 David W. Walker, Cardiff University 24 Summary n There is an active body of PSE researchers and developers in Europe. n PSEs are used in science, engineering, finance, and manufacturing. n Current emphasis is on PSE infrastructure and prototypes.

31/8/99 David W. Walker, Cardiff University 25 Future Challenges n Maintaining good, reliable performance in distributed environments important. n Need to integrate third party software. n Need visualisation environments that scale from PC up to immersive systems. n Needs standards for interfaces and interaction between PSEs.