Transcript Slajd 1 - PL-Grid

Polish Infrastructure
for Supporting Computational Science
in the European Research Space
The Capabilities of the GridSpace2
Experiment Workbench
Jan Meizner
and Distributed Computing Environments (DICE)
Team
Academic Computer Centre CYFRONET
i3: Internet - Infrastruktury - Innowacje
1-3.12.2010
EUROPEAN UNION
Motivation
 Complex scientific applications on
modern computing infrastructures

Clusters, Grids, Clouds
 Diverse software packages
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Applications (Gaussian, NAMD,…)
Web Services
Scripts: Perl, Python, Ruby
 Different users
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Chemists, biologists
Programmers
End users
 Various data types
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Files, databases, URLs
 Exploratory programming
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Unstructured, dynamic, prototyping
 Collaboration
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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 Features
Platform – as opposed to concrete application
General-purpose
Exploits Web 2.0 opportunities in facilitating
application development, operation, provisioning
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
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Experiment plan – a specification of the sequence
of activities
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 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,
Security in GridSpace2
 Connectivity via:
 HTTPS (browser <-> Experiment Workbench)
 SSH/SCP/SFTP (ExperimentWorkbench <-> Experiment Host)
 User account context on Experiment Host
 OS-level accessibility rights to files
 Snippet code can contain a „secret” literal introduced by meta-markup
<SECRET:MY_SECRET_NAME>
 During the execution this meta-markup is replaced with secret value
taken from personal secret database called Wallet
 Available Wallet implementations:
 Simple file database located on the Experiment Host
 Remote Central Wallet (ReCeW)
 ReCeW (Remote Central Wallet) – key features:
 Security – HTTPS protected REST API and AES-256 encryption
of stored credentials
 Highly efficient implementation as native (C++) application
 Extendable through plug-in mechanism (4 types of plug-ins)
Working with GridSpace2
 Easy access using Web
browser
 Experiment Workbench
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Constructing experiment
plans from code snippets
Interactively run
experiments
 Experiment Execution
Environment
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Multiple interpreters
Access to libraries,
programs and services
(gems)
 Access to computing
infrastructure
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Cluster, grid, cloud
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Application:
Analysis of water solutions of aminoacids
 Involving multiple steps realized with many
tools, langauges and libraries used for
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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
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.
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References
 http://wl.plgrid.pl
– open the Virtual Laboratory in your browser
 http://dice.cyfronet.pl/gridspace
– learn more about GridSpace technology
 http://dice.cyfronet.pl/
– Distributed Computing Environemnts Team (DICE)
website
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