EUROPEAN UNION Polish Infrastructure for Supporting Computational Science in the European Research Space The Capabilities of the GridSpace2 Experiment.

Slides:



Advertisements
Similar presentations
Polska Infrastruktura Informatycznego Wspomagania Nauki w Europejskiej Przestrzeni Badawczej Institute of Computer Science AGH ACC Cyfronet AGH The PL-Grid.
Advertisements

Software Modeling SWE5441 Lecture 3 Eng. Mohammed Timraz
Scientific Workflow Support in the PL-Grid Infrastructure with HyperFlow Bartosz Baliś, Tomasz Bartyński, Kamil Figiela, Maciej Malawski, Piotr Nowakowski,
What’s New in Office Visio 2007 Microsoft Office Visio 2007 drawing and diagramming software makes it easy for IT and business professionals to.
Polish Infrastructure for Supporting Computational Science in the European Research Space GridSpace Based Virtual Laboratory for PL-Grid Users Maciej Malawski,
© , Michael Aivazis DANSE Software Issues Michael Aivazis California Institute of Technology DANSE Software Workshop September 3-8, 2003.
Russell Taylor Lecturer in Computing & Business Studies.
Next Generation Domain-Services in PL-Grid Infrastructure for Polish Science. Numerical Simulations of Metal Forming Production Processes and Cycles by.
Chapter 10 Application Development. Chapter Goals Describe the application development process and the role of methodologies, models and tools Compare.
Types of software. Sonam Dema..
Python Introduction.
Annual SERC Research Review - Student Presentation, October 5-6, Extending Model Based System Engineering to Utilize 3D Virtual Environments Peter.
VAP What is a Virtual Application ? A virtual application is an application that has been optimized to run on virtual infrastructure. The application software.
EUROPEAN UNION Polish Infrastructure for Supporting Computational Science in the European Research Space Cracow Grid Workshop’10 Kraków, October 11-13,
EUROPEAN UNION Polish Infrastructure for Supporting Computational Science in the European Research Space Ab initio grid chemical software ports – transferring.
Cracow - CYFRONET PACKAGING pack into portable format e.g. rpm PACKAGING pack into portable format e.g. rpm PACKAGING pack into portable format e.g. rpm.
Distributed Cloud Environment for PL-Grid Applications Piotr Nowakowski, Tomasz Bartyński, Tomasz Gubała, Daniel Harężlak, Marek Kasztelnik, J. Meizner,
 Cloud computing  Workflow  Workflow lifecycle  Workflow design  Workflow tools : xcp, eucalyptus, open nebula.
EUROPEAN UNION Polish Infrastructure for Supporting Computational Science in the European Research Space The Capabilities of the GridSpace2 Experiment.
Metadata Creation with the Earth System Modeling Framework Ryan O’Kuinghttons – NESII/CIRES/NOAA Kathy Saint – NESII/CSG July 22, 2014.
Quality Attributes of Web Software Applications – Jeff Offutt By Julia Erdman SE 510 October 8, 2003.
CONTENTS Arrival Characters Definition Merits Chararterstics Workflows Wfms Workflow engine Workflows levels & categories.
Per Møldrup-Dalum State and University Library SCAPE Information Day State and University Library, Denmark, SCAPE Scalable Preservation Environments.
T.Jadczyk, Bioinformatics Applications in the Virtual Laboratory Bioinformatics Applications in the Virtual Laboratory Tomasz Jadczyk AGH University of.
Summary of distributed tools of potential use for JRA3 Dugan Witherick HPC Programmer for the Miracle Consortium University College.
Protein Molecule Simulation on the Grid G-USE in ProSim Project Tamas Kiss Joint EGGE and EDGeS Summer School.
Contents 1.Introduction, architecture 2.Live demonstration 3.Extensibility.
11 CORE Architecture Mauro Bruno, Monica Scannapieco, Carlo Vaccari, Giulia Vaste Antonino Virgillito, Diego Zardetto (Istat)
The Roadmap to Software Factories Tools, Patterns and Frameworks.
DataNet – Flexible Metadata Overlay over File Resources Daniel Harężlak 1, Marek Kasztelnik 1, Maciej Pawlik 1, Bartosz Wilk 1, Marian Bubak 1,2 1 ACC.
Bioinformatics Core Facility Guglielmo Roma January 2011.
Large Scale Nuclear Physics Calculations in a Workflow Environment and Data Provenance Capturing Fang Liu and Masha Sosonkina Scalable Computing Lab, USDOE.
EC-project number: Universal Grid Client: Grid Operation Invoker Tomasz Bartyński 1, Marian Bubak 1,2 Tomasz Gubała 1,3, Maciej Malawski 1,2 1 Academic.
Workflow in Grid Systems Workshop Dave Berry, Research Manager UK National e-Science Centre GGF10, Mar 2004.
1 The Mapper project receives funding from the EC's Seventh Framework Programme (FP7/ ) under grant agreement n° RI Towards Environment.
Moby Web Services Iván Párraga García MSc on Bioinformatics for Health Sciences May 2006.
11 CORE Architecture Mauro Bruno, Monica Scannapieco, Carlo Vaccari, Giulia Vaste Antonino Virgillito, Diego Zardetto (Istat)
Chapter 6 CASE Tools Software Engineering Chapter 6-- CASE TOOLS
EGEE-III INFSO-RI Enabling Grids for E-sciencE EGEE and gLite are registered trademarks Grid Web Portal for Chemists M. Sterzel,
Lightweight construction of rich scientific applications Daniel Harężlak(1), Marek Kasztelnik(1), Maciej Pawlik(1), Bartosz Wilk(1) and Marian Bubak(1,
Federating PL-Grid Computational Resources with the Atmosphere Cloud Platform Piotr Nowakowski, Marek Kasztelnik, Tomasz Bartyński, Tomasz Gubała, Daniel.
Mantid Stakeholder Review Nick Draper 01/11/2007.
JavaScript 101 Introduction to Programming. Topics What is programming? The common elements found in most programming languages Introduction to JavaScript.
Polish Infrastructure for Supporting Computational Science in the European Research Space EUROPEAN UNION Examining Protein Folding Process Simulation and.
Portals and my Grid Stefan Rennick Egglestone Mixed Reality Laboratory University of Nottingham.
From Use Cases to Implementation 1. Structural and Behavioral Aspects of Collaborations  Two aspects of Collaborations Structural – specifies the static.
INFSO-RI JRA2 Test Management Tools Eva Takacs (4D SOFT) ETICS 2 Final Review Brussels - 11 May 2010.
Continuous Delivery and Team Foundation Server 2013 Ognjen Bajić Ana Roje Ivančić Ekobit.
The Mapper project receives funding from the EC's Seventh Framework Programme (FP7/ ) under grant agreement n° RI CYFRONET Hands.
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.
InSilicoLab – Grid Environment for Supporting Numerical Experiments in Chemistry Joanna Kocot, Daniel Harężlak, Klemens Noga, Mariusz Sterzel, Tomasz Szepieniec.
EGI-InSPIRE RI EGI Compute and Data Services for Open Access in H2020 Tiziana Ferrari Technical Director, EGI.eu
EGEE-II INFSO-RI Enabling Grids for E-sciencE EGEE and gLite are registered trademarks Computational Chemistry Cluster – EGEE-III.
PLG-Data and rimrock Services as Building
Seasonal School Demo and Assigments
IBM Predictive Analytics Virtual Users’ Group Meeting March 30, 2016
Pasquale Pagano (CNR-ISTI) Project technical director
Integrating Scientific Tools and Web Portals
MIRACLE Cloud-based reproducible data analysis and visualization for outputs of agent-based models Xiongbing Jin, Kirsten Robinson, Allen Lee, Gary Polhill,
Model Execution Environment for Investigation of Heart Valve Diseases
A Collaborative Environment Allowing Clinical Investigations on Integrated Biomedical Databases Matthias Assel HealthGrid 2009.
DICE - Distributed Computing Environments Team
Recap: introduction to e-science
PROCESS - H2020 Project Work Package WP6 JRA3
Module 01 ETICS Overview ETICS Online Tutorials
Mariusz Sterzel1 , Lukasz Dutka1, Tomasz Szepieniec1
The ViroLab Virtual Laboratory for Viral Diseases
A Survey of Interactive Execution Environments
What is UiPATH? For more details visit this link online-training.
Presentation transcript:

EUROPEAN UNION Polish Infrastructure for Supporting Computational Science in the European Research Space The Capabilities of the GridSpace2 Experiment Workbench M. Bubak, E. Ciepiela, J. Kocot, J. Meizner, and P. Nowakowski Distributed Computing Environments Team Academic Computer Centre CYFRONET Cracow Grid Workshop

Motivation  Complex scientific applications on modern computing infrastructures  Clusters, Grids, Clouds  Diverse software packages  Applications (Gaussian, NAMD,…)  Web Services  Scripts: Perl, Python, Ruby  Different users  Chemists, biologists  Programmers  End users  Various data types  Files, databases, URLs  Exploratory programming  Unstructured, dynamic, prototyping  Collaboration  Teams, communities

GridSpace2 Objectives  Facilitate dealing with application throughout its entire lifecycle (development, deployment, sharing, operation, maintenance) from single “workbench” where all available software is integrated  Reflect and support a natural daily style of work with a suite of software – workflows, (not formalized) procedures, task paths etc.  Addresses a specific type of application called experiments

GridSpace2 Experiment  Experiment - a process that combines a sequence of activities (usage of programs, services) that act on input data in order to produce experiment results  Experiment plan – a specification of the sequence of activites  Experiment run – an enactment of the experiment plan on particular input data, producing particular results  Complex workflow going beyond manual simple and repeatable execution of single programs  Exploratory programming  Unstructured, dynamic, prototyping, further activities not known a priori

GridSpace2 Features  Platform – as opposed to concrete application  General-purpose  Exploits Web 2.0 opportunities in facilitating application development, operation, provisioning

GridSpace2 Experiment Plan  Combines steps realized on a range of software environments, platforms, tools, languages etc  Developed, shared and reused collaboratively amongst ad-hoc researching teams  Composed of collaboratively owned libraries and services used (called gems) and experiment parts (called snippets)

Exploratory Programming  Involves experimentation and exploring – step by step programming where steps are likely not known in advance but rather provided ad-hoc basing on the results of previous ones  Experiment needs to be re-enacted many times with some ad-hoc customization made dynamically while the workflow enactment has already started  Cannot be fully automated and needs continuous supervision, validation or even intrusion  Dynamic nature of experiment plan – certain decisions taken at runtime (e.g. code provided from input data)  But: Despite its indirect development process experiment still needs to be traceable, verifiable, easily re-runnable and its outcome – straightforwardly reproducible,

8 Working with GridSpace2  Easy access using Web browser  Experiment Workbench  Constructing experiment plans from code snippets  Interactively run experiments  Experiment Execution Environment  Multiple interpreters  Access to libraries, programs and services (gems)  Access to computing infrastructure  Cluster, grid, cloud

Application: Analysis of water solutions of aminoacids  Involving multiple steps realized with many tools, langauges and libraries used for  Packmol – molecular dynamics simulations of packing molecules in a defined regions of space  Jmol – visualization of solution  Gaussian – computing a spectrum of the solution  Python/CCLIB – extracting spectrum info  jqPlot – displaying plot Collaboration with computational chemists of ACC Cyfronet AGH and Departament of Chemistry, Jagiellonian University, Dr. Mariusz Sterzel, Klemens Noga

10 Conclusions  Complex scientific applications need dedicated tools and approaches.  In-silico experiments are supported by Virtual Laboratory powered by GridSpace2 technology.  Applications:  Bioinformatics  Computational chemistry  More are welcome!  Virtual laboratory is open for PL-Grid users.

11 References  – open the Virtual Laboratory in your browser  – learn more about GridSpace technology  – Distributed Computing Environemnts Team (DICE) website