In this paper, we present the computational task-management tool Ganga, which allows for the specification, submission, bookkeeping and post-processing of computational tasks on a wide set of ...distributed resources. Ganga has been developed to solve a problem increasingly common in scientific projects, which is that researchers must regularly switch between different processing systems, each with its own command set, to complete their computational tasks. Ganga provides a homogeneous environment for processing data on heterogeneous resources. We give examples from High Energy Physics, demonstrating how an analysis can be developed on a local system and then transparently moved to a Grid system for processing of all available data. Ganga has an API that can be used via an interactive interface, in scripts, or through a GUI. Specific knowledge about types of tasks or computational resources is provided at run-time through a plugin system, making new developments easy to integrate. We give an overview of the Ganga architecture, give examples of current use, and demonstrate how Ganga can be used in many different areas of science.
Program title:Ganga
Catalogue identifier: AEEN_v1_0
Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEEN_v1_0.html
Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland
Licensing provisions: GPL
No. of lines in distributed program, including test data, etc.: 224 590
No. of bytes in distributed program, including test data, etc.: 14 365 315
Distribution format: tar.gz
Programming language: Python
Computer: personal computers, laptops
Operating system: Linux/Unix
RAM: 1 MB
Classification: 6.2, 6.5
Nature of problem: Management of computational tasks for scientific applications on heterogenous distributed systems, including local, batch farms, opportunistic clusters and Grids.
Solution method: High-level job management interface, including command line, scripting and GUI components.
Restrictions: Access to the distributed resources depends on the installed, 3rd party software such as batch system client or Grid user interface.
The FORTRAN code POLRAD 2.0 for radiative correction calculation in inclusive and semi-inclusive deep inelastic scattering of polarized leptons by polarized nucleons and nuclei is described. Its ...theoretical basis, structure and algorithms are discussed in detail.
An approach to calculate radiative corrections to the unpolarized cross section of semi-inclusive electroproduction is developed. Explicit formulae for the lowest order QED radiative correction are ...presented. A detailed numerical analysis is performed with the kinematics of experiments with fixed targets.
Ganga has been widely used for several years in ATLAS, LHCb and a handful of other communities. Ganga provides a simple yet powerful interface for submitting and managing jobs to a variety of ...computing backends. The tool helps users configuring applications and keeping track of their work. With the major release of version 5 in summer 2008, Ganga's main user-friendly features have been strengthened. Examples include a new configuration interface, enhanced support for job collections, bulk operations and easier access to subjobs. In addition to the traditional batch and Grid backends such as Condor, LSF, PBS, gLite/EDG a point-to-point job execution via ssh on remote machines is now supported. Ganga is used as an interactive job submission interface for end-users, and also as a job submission component for higher-level tools. For example GangaRobot is used to perform automated, end-to-end testing of distributed data analysis. Ganga comes with an extensive test suite covering more than 350 test cases. The development model involves all active developers in the release management shifts which is an important and novel approach for the distributed software collaborations. Ganga 5 is a mature, stable and widely-used tool with long-term support from the HEP community.
Electronic mentoring as an innovative technology in training is becoming increasingly popular in the public service. To this end, the authors of this paper have developed a conceptual framework for ...an intra-organizational learning environment based on the use of game modeling that would promote professional development and personnel evaluation. The basis of the intra-organizational learning environment design is the methodology of visual graphical modeling and the method of production rules construction. The learning environment ensures the variability and continuity of educational programs organized by position and by personnel procedures. In the course of preliminary testing, an initial measurement of the employee’s professional competencies is performed, followed by comparison with the professional competencies expected for that particular position and the assessment of changes. The results of the assessment are transferred to a visual graphical model. Based on the results of the assessment, the system automatically puts the employee on reserve or assigns them a training program. The training process for a particular position is based on the principles of “learning through playing” and visual imitation. The passage of personnel procedures is based on a sequence of production rules; the application of gaming techniques means that the proposed scenarios are not the product of an abstract generalization, but a real personnel procedure. The article considers the problems and features of modeling the educational environment, as well as the experience of the research team of the Moscow Technological University in the development of production rules and the creation of simulators for civil servants to develop regulations and acquire new skills.
LHCb distributed computing and the GRID Brook, N.; Bulten, H.; Closier, J. ...
Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment,
04/2003, Letnik:
502, Številka:
2
Journal Article
Recenzirano
Odprti dostop
The current architecture of the LHCb distributed system for Monte Carlo data production is described. An overview is given of the current and planned use of Grid technology from the European Datagrid ...Project, and of the development of an experiment-specific user interface to Grid services.
Atom-optics hologram in the time domain Soroko, A. V.
Physical review. A, Atomic, molecular, and optical physics,
07/2000, Letnik:
62, Številka:
1
Journal Article
The distributed data analysis using Grid resources is one of the fundamental applications in high energy physics to be addressed and realized before the start of LHC data taking. The need to ...facilitate the access to the resources is very high. In every experiment up to a thousand physicist will be submitting analysis jobs into the Grid. Appropriate user interfaces and helper applications have to be made available to assure that all users can use the Grid without too much expertise in Grid technology. These tools enlarge the number of grid users from a few production administrators to potentially all participating physicists. The GANGA job management system (http://cern.ch/ganga), developed as a common project between the ATLAS and LHCb experiments provides and integrates these kind of tools. GANGA provides a simple and consistent way of preparing, organizing and executing analysis tasks within the experiment analysis framework, implemented through a plug-in system. It allows trivial switching between running test jobs on a local batch system and running large-scale analyzes on the Grid, hiding Grid technicalities. We will be reporting on the plug-ins and our experiences of distributed data analysis using GANGA within the ATLAS experiment and the EGEE/LCG infrastructure. The integration with the ATLAS data management system DQ2 into GANGA is a key functionality. In combination with the job splitting mechanism large amounts of jobs can be sent to the locations of data following the ATLAS computing model. GANGA supports tasks of user analysis with reconstructed data and small scale production of Monte Carlo data.
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