DOCSLIB.ORG

Scalable Audio Processing Across Heterogeneous Distributed Resources an Investigation Into Distributed Audio Processing for Music Information Retrieval

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Scalable Audio Processing Across Heterogeneous Distributed Resources an Investigation Into Distributed Audio Processing for Music Information Retrieval Scalable Audio Processing Across Heterogeneous Distributed Resources An Investigation into Distributed Audio Processing for Music Information Retrieval Ahmad Al-Shakarchi School of Computer Science, Cardiff University ii Declaration This work has not previously been accepted in substance for any degree and is not con- currently submitted in candidature for any degree. Signed ............................................. (candidate) Date ......................... STATEMENT 1 This thesis is being submitted in partial fulfillment of the requirements for the degree of Ph.D. Signed ............................................. (candidate) Date ......................... STATEMENT 2 This thesis is the result of my own independent work/investigation, except where oth- erwise stated. Other sources are acknowledged by explicit references. Signed ............................................. (candidate) Date ......................... STATEMENT 3 I hereby give consent for my thesis, if accepted, to be available for photocopying and for inter-library loan, and for the title and summary to be made available to outside or- ganisations. Signed ............................................. (candidate) Date ......................... iii iv Acknowledgements The work presented in this thesis could not have been completed without the help and support of various researchers, scientists, family members and close friends that I am fortunate enough to have in my life. I would like to thank the Triana developers and researchers that I have worked closely with during my time as a PhD student, and that built the foundation for my work; Dr. Matthew Shields, Dr. Andrew Harrison, and Dr. Ian Wang. Extra special thanks are extended to Kieran Evans at Cardiff University for his help and expertise - I am eternally indebted! I am also particularly grateful for the assistance of researchers and developers at var- ious institutes around the world that helped me conduct such large scale experiments - researchers at: Laboratoire de l'Acc´el´erateurLin´eaire(Paris, France), SZTAKI (Hungarian Academy of the Sciences, Hungary), the Information Sciences Institute at the University of Southern California and the Center for Computation and Technology at Louisiana State University (USA), the University of Coimbra (Portugal), and not forgetting researchers and staff at Cardiff University. I would like to thank the Computer Science and Informatics department at Cardiff for allowing me the opportunity to perform this research. I would - of course - like to extend a very special `thank you' to my supervisor Dr. Ian Taylor, for his patience, his ongoing dedication to my work, his vision and superior intellect (!), and most of all his friendship throughout my PhD. Thank you for all the cool opportunities you've provided me! I could not have asked for a better and more understanding supervisor and am happy to have developed a great friend over the years. Rock on! To my label mates and closest associates; Dan, Ruff, Ralph, Mud and Huw, who may v not know too much about my academic career, but whose antics have provided me with the levity required to maintain my sanity1 over the years. Thank you! To Sarah, who sacrificed so much and showed massive commitment, love and support to me. You helped me more than you know and I will never forget it. I'm also indebted to the entire Kingman family - especially Roger and Gaynor - for their support during hard times. Finally, I would like to thank my family - Ali, Israa, Khitam, Mazin - for supporting me in every way imaginable; I know I asked too much of you all and hope I can repay you with unwavering love, support and patience, in turn. Especially to my father, for whom all of my work and perseverance was really for. Thank you, dad. 1Relatively speaking. vi Abstract Audio analysis algorithms and frameworks for Music Information Retrieval (MIR) are expanding rapidly, providing new ways to discover non-trivial information from audio sources, beyond that which can be ascertained from unreliable metadata such as ID3 tags. MIR is a broad field and many aspects of the algorithms and analysis components that are used are more accurate given a larger dataset for analysis, and often require extensive computational resources. This thesis investigates if, through the use of modern distributed computing techniques, it is possible to design an MIR system that is scalable as the number of participants in- creases, which adheres to copyright laws and restrictions, whilst at the same time enabling access to a global database of music for MIR applications and research. A scalable platform for MIR analysis would be of benefit to the MIR and scientific community as a whole. A distributed MIR platform that encompasses the creation of MIR algorithms and workflows, their distribution, results collection and analysis, is presented in this thesis. The framework, called DART - Distributed Audio Retrieval using Triana - is designed to facilitate the submission of MIR algorithms and computational tasks against either remotely held music and audio content, or audio provided and distributed by the MIR researcher. Initially a detailed distributed DART architecture is presented, along with simulations to evaluate the validity and scalability of the architecture. The idea of a pa- rameter sweep experiment to find the optimal parameters of the Sub-Harmonic Summation (SHS) algorithm is presented, in order to test the platform and use it to perform useful and real-world experiments that contribute new knowledge to the field. DART is tested on various pre-existing distributed computing platforms and the feasi- bility of creating a scalable infrastructure for workflow distribution is investigated through- vii out the thesis, along with the different workflow distribution platforms that could be inte- grated into the system. The DART parameter sweep experiments begin on a small scale, working up towards the goal of running experiments on thousands of nodes, in order to truly evaluate the scalability of the DART system. The result of this research is a functional and scalable distributed MIR research platform that is capable of performing real world MIR analysis, as demonstrated by the successful completion of several large scale SHS parameter sweep experiments across a variety of dif- ferent input data - using various distribution methods - and through finding the optimal parameters of the implemented SHS algorithm. DART is shown to be highly adaptable both in terms of the distributed MIR analysis algorithm, as well as the distribution mech- anism used. viii Contents 1 Introduction 1 1.0.1 Overview . .1 1.0.2 Hypothesis and Research Question . .4 1.0.3 Approach . .5 1.0.4 Contributions to the State of the Art . .5 1.0.5 Project History . .7 1.0.6 Layout & chapter plan/thesis outline . .7 2 Background 11 2.1 Overview . 11 2.2 Review of Musical Concepts . 12 2.2.1 Sound . 12 2.2.2 Pitch . 12 2.2.3 Intensity . 14 2.2.4 Timbre . 14 2.3 Digital Audio . 15 2.3.1 Digital Signal Processing . 15 2.3.2 Analog and digital signals . 16 2.3.3 Sampling . 16 2.3.4 Time domain representation . 18 2.3.5 Frequency Domain Representation . 18 2.3.6 Fourier Transform . 19 2.3.7 Why the Frequency Domain? . 23 2.4 Pitch Detection Algorithms . 24 2.4.1 Time Domain Pitch Detection . 25 ix CONTENTS 2.4.2 Frequency Domain Pitch Detection . 26 2.5 Music Information Retrieval . 30 2.5.1 Distributed MIR systems . 33 2.5.2 Music Recommendation Systems . 35 2.6 Triana Programming Environment . 39 2.6.1 Triana Data Types . 40 2.6.2 Audio Toolkit . 42 2.6.3 Creating and Running Triana Programs . 46 2.6.4 Related Music Data-flow Tools . 47 2.6.5 JavaSound API . 51 3 Requirements Analysis, Underlying Infrastructures and Architecture 55 3.1 DART Overview . 55 3.2 Investigation into the Use of a P2P Architecture . 62 3.2.1 Peer to Peer Computing . 62 3.2.2 A P2P DART Case Study . 64 3.2.3 Proposed Work Package Assignment and Results Retrieval Archi- tecture . 66 3.2.4 Peer Overview . 70 3.2.5 Workflow Design . 71 3.3 Simulation Results . 71 3.3.1 Distributed Simulations . 71 3.4 Conclusions . 77 3.4.1 P2P Technology Feasibility . 77 3.5 Relevant Distributed Computing Technologies . 80 3.5.1 XtremWeb . 80 3.5.2 EGEE / EGI . 83 3.5.3 GRID5000 . 84 3.5.4 BOINC . 85 3.5.5 AtticFS . 89 3.5.6 Distributed Computing Summary . 89 4 Design 91 4.1 Chapter Overview . 91 x CONTENTS 4.2 Design Overview . 92 4.3 The Sub-Harmonic Summation Algorithm and Triana . 93 4.3.1 LoadSound Unit . 94 4.3.2 Fast Fourier Transform Unit . 95 4.3.3 OneSide . 97 4.3.4 AmplitudeSpectrum . 97 4.3.5 PitchDetection . 97 4.3.6 NoteMapper . 98 4.3.7 Unit Design . 98 4.4 Mapping Triana Workflows to the DART Execution Environment . 100 4.4.1 Analysis of Triana Application Structure . 102 4.4.2 Designing a standalone Triana Workflow framework application . 103 4.4.3 User Interface . 105 4.5 DART Experiment Design Choices . 106 4.5.1 Experiment Design Overview . 107 4.6 Input Data Design . 111 4.6.1 Acoustic Guitar . 112 4.6.2 Distorted Guitar . 113 4.6.3 Oboe . 114 4.6.4 Grand Piano . 114 4.6.5 Violin . 115 4.6.6 Tubular Bells . 115 4.6.7 Input Data Design Summary . 116 4.7 Requirements Analysis . 116 4.8 Distribution of Workflows . 119 4.8.1 XtremWeb . 120 4.8.2 BOINC . 121 4.9 Results Analysis . 122 4.9.1 Comparison of Distribution Platforms . 124 4.10 Summary . ..
Load more

Recommended publications
  • "Challenges and Formal Aspects of Volunteer Computing"
    BUDAPEST UNIVERSITY OF TECHNOLOGY AND ECONOMICS FACULTY OF ELECTRICAL ENGINEERING AND INFORMATICS DEPARTMENT OF AUTOMATION AND APPLIED INFORMATICS Attila Csaba Marosi Önkéntes Számítási Rendszerek Kihívásai és Formális Aspektusai Challenges and Formal Aspects of Volunteer Computing Ph.D. Thesis Thesis Advisors: Péter Kacsuk MTA SZTAKI, LPDS Sándor Juhász BME, AUT Budapest, 2016. ‘‘The important thing is not to stop questioning. Curiosity has its own reason for existing. One cannot help but be in awe when he contemplates the mysteries of eternity, of life, of the marvelous structure of reality. It is enough if one tries merely to comprehend a little of this mystery every day. Never lose a holy curiosity.’’ -- Albert Einstein Abstract Volunteer Computing (VC) and Desktop Grid (DG) systems collect and make available the donated the resources from non-dedicated computers like office and home desktops. VC systems are usually deployed to solve a grand compute intensive problem by researchers who either don’t have access to or don’t have the resources to buy a dedicated infrastruc- ture; or simply don’t want to maintain such an infrastructure. VC and DG paradigms seem similar, however they target different use cases and environments: DG systems operate within the boundaries of institutes, while VC systems collect resources from the publicly accessible internet. Evidently VC resembles DGs whereas DGs are not fully equivalent to VC. Contrary to “traditional grids” [1,2] there is no formal definition for the relationship of DG and VC that could be used to categorize existing systems. There are informal at- tempts to categorize them and compare with grid systems [3,4,5].
    [Show full text]
  • The Social Cloud for Public Eresearch
    The Social Cloud for Public eResearch by Koshy John A thesis submitted to the Victoria University of Wellington in fulfilment of the requirements for the degree of Master of Engineering in Network Engineering. Victoria University of Wellington 2012 Abstract Scientific researchers faced with extremely large computations or the re- quirement of storing vast quantities of data have come to rely on dis- tributed computational models like grid and cloud computing. However, distributed computation is typically complex and expensive. The Social Cloud for Public eResearch aims to provide researchers with a platform to exploit social networks to reach out to users who would otherwise be unlikely to donate computational time for scientific and other research ori- ented projects. This thesis explores the motivations of users to contribute computational time and examines the various ways these motivations can be catered to through established social networks. We specifically look at integrating Facebook and BOINC, and discuss the architecture of the functional system and the novel social engineering algorithms that power it. ii Acknowledgments I would first like to thank my parents, John Koshy and Susan John, for their unwavering love and support in all my endeavours. I would like to thank my supervisor, Kris Bubendorfer, for his valuable guidance and support throughout my thesis. Kyle Chard and Ben Palmer have my thanks for their contributions and feedback in the course of au- thoring the IEEE e-Science paper on the Social Cloud for Public eResearch. Many thanks are also due to Andy Linton for his help with managing the development and test server for the Social Cloud for Public eResearch.
    [Show full text]
  • Toward Crowdsourced Drug Discovery: Start-Up of the Volunteer Computing Project Sidock@Home
    Toward crowdsourced drug discovery: start-up of the volunteer computing project SiDock@home Natalia Nikitina1[0000-0002-0538-2939] , Maxim Manzyuk2[000-0002-6628-0119], Marko Juki´c3;4[0000-0001-6083-5024], Crtomirˇ Podlipnik5[0000-0002-8429-0273], Ilya Kurochkin6[0000-0002-0399-6208], and Alexander Albertian6[0000-0002-6586-8930] 1 Institute of Applied Mathematical Research, Karelian Research Center of the Russian Academy of Sciences, Petrozavodsk, Russia, [email protected] 2 Internet portal BOINC.ru, Moscow, Russia, [email protected] 3 Chemistry and Chemical Engineering, University of Maribor, Maribor, Slovenia 4 Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Koper, Slovenia [email protected] 5 Faculty of Chemistry and Chemical Technology, University of Ljubljana, Ljubljana, Slovenia, [email protected] 6 Federal Research Center \Computer Science and Control" of the Russian Academy of Sciences, Moscow, Russia, [email protected], [email protected], [email protected] Abstract. In this paper, we describe the experience of setting up a computational infrastructure based on BOINC middleware and running a volunteer computing project on its basis. We characterize the first series of computational experiments and review the project's development in its first six months. The gathered experience shows that BOINC-based Desktop Grids allow to to efficiently aid drug discovery at its early stages. Keywords: Desktop Grid · Distributed computing · Volunteer comput- ing · BOINC · Virtual drug screening · Molecular docking · SARS-CoV-2 1 Introduction Among the variety of high-performance computing (HPC) systems, Desktop Grids hold a special place due to their enormous potential and, at the same time, high availability.
    [Show full text]
  • Multiagent Social Computing
    56 International Journal of Web Portals, 3(4), 56-68, October-December 2011 Multiagent Social Computing Ben Choi, Louisiana Tech University, USA ABSTRACT This article provides a framework for extending social networks to social computing. When people join social networks, such as Facebook and discussion groups, their personal computers can also join the social networks. This framework facilitates sharing of computing resources among friends and groups. Computers of friends and groups act autonomously to help each other perform various tasks. The framework combines many key technologies, including intelligent agents, multi-agent system, object space, and parallel and distributed computing, into a new computing platform, which has been successfully implemented and tested. With this framework, any person will have access to not only the computing power of his or her own personal computer but also the vast computing power of a community of computers. The collective capabilities of humans and computers working in communities will create complementary capabilities of computing to achieve behaviors that transcend those of people and computers in isolation. The future of computing is moving from personal computers to societies of computers. Keywords: Cloud Computing, Intelligent Agents, Multi-Agent System, Parallel Distributed Processing, Social Computing, Social Network INTRODUCTION Internet can join computing communities and so does any networked computers, creating social This article extends the concept of socially computing systems ranging
    [Show full text]
  • Addressing Selfishness in the Design of Cooperative Systems Guido Lena Cota
    Addressing selfishness in the design of cooperative systems Guido Lena Cota To cite this version: Guido Lena Cota. Addressing selfishness in the design of cooperative systems. Computer Science and Game Theory [cs.GT]. Université de Lyon; Università degli studi (Milan, Italie). Convegno di studi (2000 ; Milano), 2017. English. NNT : 2017LYSEI023. tel-02191480 HAL Id: tel-02191480 https://tel.archives-ouvertes.fr/tel-02191480 Submitted on 23 Jul 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. NNT : 2017LYSEI023 DOCTORAL THESIS Cotutelle-de-thèse INSTITUT NATIONAL DES SCIENCES APPLIQUÉES DE LYON ÉCOLE DOCTORALE ED 512 – INFORMATIQUE ET MATHÉMATIQUES DE LYON SPÉCIALITÉ INFORMATIQUE DIRECTOR: PROF. LUCA Q. ZAMBONI UNIVERSITÁ DEGLI STUDI DI MILANO DEPARTMENT OF COMPUTER SCIENCE CORSO DI DOTTORATO IN INFORMATICA (XXVIII CYCLE) – INF/01 COORDINATOR: PROF. PAOLO BOLDI Defended on 24 March 2017, by : Guido LENA COTA Addressing Selfishness in the Design of Cooperative Systems Supervisors: Prof. Lionel BRUNIE INSA de Lyon Prof. Ernesto DAMIANI Università degli Studi di Milano Cosupervisors: Dr. Sonia BEN MOKHTAR INSA de Lyon Dr. Gabriele GIANINI Università degli Studi di Milano EXAMINATION COMMITTEE: Reviewers: Prof. Harald KOSCH Universität Passau, Germany Prof.
    [Show full text]
  • BOINC: a Platform for Volunteer Computing
    BOINC: A Platform for Volunteer Computing David P. Anderson University of California, Berkeley Space Sciences Laboratory Berkeley, CA 94720 [email protected] December 9, 2018 Abstract “Volunteer computing” is the use of consumer digital devices for high-throughput scientific computing. It can provide large computing capacity at low cost, but presents challenges due to device heterogeneity, unreliability, and churn. BOINC, a widely-used open-source middleware system for volunteer computing, addresses these challenges. We describe its features, architecture, and implementation. Keywords BOINC, volunteer computing, distributed computing, scientific computing, high-throughput computing 1. Introduction 1.1 Volunteer computing Volunteer computing (VC) is the use of consumer digital devices, such as desktop and laptop computers, tablets, and smartphones, for high-throughput scientific computing. Device owners participate in VC by installing a program that downloads and executes jobs from servers operated by science projects. There are currently about 30 VC projects in many scientific areas and at many institutions. The research enabled by VC has resulted in numerous papers in Nature, Science, PNAS, Physical Review, Proteins, PloS Biology, Bioinformatics, J. of Mol. Biol., J. Chem. Phys, and other top journals [1]. About 700,000 devices are actively participating in VC projects. These devices have about 4 million CPU cores and 560,000 GPUs, and collectively provide an average throughput of 93 PetaFLOPS. The devices are primarily modern, high-end computers: they average 16.5 CPU GigaFLOPS and 11.4 GB of RAM, and most have a GPU capable of general-purpose computing using OpenCL or CUDA. 1 The potential capacity of VC is much larger: there are more than 2 billion consumer desktop and laptop computers [2].
    [Show full text]
  • Addressing Selfishness in the Design of Cooperative Systems
    DOCTORAL THESIS Cotutelle-de-thèse INSTITUT NATIONAL DES SCIENCES APPLIQUÉES DE LYON ÉCOLE DOCTORALE ED 512 – INFORMATIQUE ET MATHÉMATIQUES DE LYON SPÉCIALITÉ INFORMATIQUE DIRECTOR: PROF. LUCA Q. ZAMBONI UNIVERSITÁ DEGLI STUDI DI MILANO DEPARTMENT OF COMPUTER SCIENCE CORSO DI DOTTORATO IN INFORMATICA (XXVIII CYCLE) – INF/01 COORDINATOR: PROF. PAOLO BOLDI Defended on 24 March 2017, by : Guido LENA COTA Addressing Selfishness in the Design of Cooperative Systems Supervisors: Prof. Lionel BRUNIE INSA de Lyon Prof. Ernesto DAMIANI Università degli Studi di Milano Cosupervisors: Dr. Sonia BEN MOKHTAR INSA de Lyon Dr. Gabriele GIANINI Università degli Studi di Milano EXAMINATION COMMITTEE: Reviewers: Prof. Harald KOSCH Universität Passau, Germany Prof. Vivien QUEMA Grenoble INP / ENSIMAG, France Reviewer (Università degli Studi di Milano) , Examiner: Dr. Julia LAWALL Sorbonne Universités, UPMC, LIP6, France Examiners: Prof. Sara BOUCHENAK INSA de Lyon, France Prof. Paola BONIZZONI Università degli Studi di Milano-Bicocca, Italy Prof. Mariagrazia FUGINI Politecnico di Milano, Italy ABSTRACT Cooperative distributed systems, particularly peer-to-peer systems, are the basis of several mainstream Internet applications (e.g., file-sharing, media streaming) and the key enablers of new and emerging technologies, including Blockchain and the Internet of Things. Essential to the success of cooperative systems is that nodes are willing to cooperate with each other by sharing part of their resources, e.g., network bandwidth, CPU capability, storage space. How- ever, as nodes are autonomous entities, they may be tempted to behave in a selfish manner by not contributing their fair share, potentially causing system performance degradation and insta- bility. Addressing selfish nodes is, therefore, key to building efficient and reliable cooperative systems.
    [Show full text]
  • The 10Th BOINC Workshop
    The 10th BOINC Workshop David P. Anderson Space Sciences Lab University of California, Berkeley 29 Sept. 2014 1985 ● Wisconsin UC Berkeley ● Internet as backplane 1987 ● Marionette 1992 ● Industry 1995 ● David Gedye: SETI@home idea 1998 ● SETI@home development – Eric Korpela – Jeff Cobb – Matt Lebofsky 1999 ● SETI@home launch 2000 ● Infrastructure issues ● United Devices 2001 ● United Devices falling-out 2002 ● ClimatePrediction.net: Myles Allen ● BOINC computing power Scientists Volunteers education/outreach 2002 ● Open source software ● Credit ● Replication and validation ● Client job buffer ● Code signing 2002 ● Hiram Clawson, Eric Heien ● NSF proposal – Mari Maeda, Kevin Thompson ● Visit Climateprediction – Carl Christensen, Tolu Aina ● Derrick Kondo ● Vijay Pande 2003 ● UD lawsuit ● Undergrads, PHP code ● Karl Chen, Mr. Python ● Oct: LIGO, Bruce Allen ● Nov: CERN – Francois Grey, Ben Segal ● Nov: WCG kicks tires 2003 job creation MySQL assimilator server scheduler validator transitioner 2004 ● Rom Walton ● Charlie Fenton 2004 ● Anonymous platform ● Separate GUI ● Cross-project ID and credit ● Preemptive scheduling ● Sticky files ● Upload/download hierarchies ● DB as buffer 2004 ● Predictor@home, Michela Taufer – homogeneous redundancy ● SETI@home: Eric Korpela ● BURP: Janus Kristensen ● Climateprediction.net launch ● LHC@home launch 2004 2004 ● Supercomputer 04 talk ● Matt Blumberg, account manager design 2005 ● Einstein@home – Reinhard Prix, Bernd Machenschalk, Oliver Bock ● Primegrid – Rytis Slatkevičius ● Rosetta@home ● IBM World
    [Show full text]
  • Universitat De Val`Encia Distributed Computing and Farm Management
    Universitat de Val`encia Departament de F´ısica Te`orica Distributed computing and farm management with application to the search for heavy gauge bosons using the ATLAS experiment at the LHC (CERN) CERN-THESIS-2008-056 21/01/2008 Tesis de Doctorado Juan Antonio Lopez-Perez 2007 CONTENTS Preface 9 Prefacio 13 I Introduction 17 1 CERN, LHC and ATLAS 19 1.1 CERN . 19 1.1.1 Discoveries and research fields . 20 1.2 The LHC . 22 1.3 The ATLAS experiment . 25 1.3.1 ATLAS sub-detectors . 27 1.3.2 ATLAS performance . 32 1.3.3 ATLAS software . 35 2 The Standard Model and Extra Dimensions 41 2.1 The Standard Model . 41 2.2 Beyond the Standard Model . 43 2.3 Extra dimensions . 45 3 Distributed Grid computing 49 3.1 The Grid . 49 3.1.1 Definition . 49 3.1.2 Some key concepts . 51 3.1.3 Middleware components . 52 3 4 3.1.4 The Globus toolkit . 53 3.1.5 Overview of a Grid job . 54 3.1.6 Challenges and benefits of the Grid . 55 3.1.7 Different kinds of Grids . 57 3.2 LHC Computing Grid . 59 3.2.1 The LCG project . 59 3.2.2 The EGEE project . 61 3.2.3 The EDG project . 63 3.2.4 The Quattor software management tool . 64 3.3 The BOINC distributed computing environment . 66 3.3.1 Overview of a BOINC job . 67 3.3.2 BOINC credit system . 68 3.3.3 The future of BOINC .
    [Show full text]
  • Idgf-Sp D221
    International Desktop Grid Federation – Support Project Contract number: RI-312297 Production, Development, Test, and Validation Infrastructure Project deliverable: D2.2.1 Due date of deliverable: 31/07/2013 Actual submission date: 31/07/2013 Lead beneficiary: MTA SZTAKI Workpackage: WP2 - Supporting infrastructure Dissemination Level: PU (Public) Version: 1.4 (FINAL) IDGF-SP is supported by the FP7 Capacities Programme under contract nr RI-312297. D2.2.1 – Production, Development, Test and Validation Infrastructure Copyright (c) 2013. Members of IDGF-SP consortium, see http://idgf-sp.eu/partners for details on the copyright holders. You are permitted to copy and distribute verbatim copies of this document containing this copyright notice but modifying this document is not allowed. You are permitted to copy this document in whole or in part into other documents if you attach the following reference to the copied elements: ‘Copyright (c) 2013. Members of IDGF-SP consortium - http://idgf-sp.eu’. The commercial use of any information contained in this document may require a license from the proprietor of that information. The IDGF-SP consortium members do not warrant that the information contained in the deliverable is capable of use, or that use of the information is free from risk, and accept no liability for loss or damage suffered by any person and organisation using this information. WP2 Copyright (c) 2013. Members of IDGF-SP consortium - http://idgf-sp.eu 2/65 D2.2.1 – Production, Development, Test and Validation Infrastructure 1 Table of Contents 1 Table of Contents ............................................................................................................ 3 2 Status and Change History .............................................................................................. 5 3 Glossary .........................................................................................................................
    [Show full text]
  • Report on Best Practices in Infrastructure Support
    International Desktop Grid Federation – Support Project Contract number: RI-312297 Report on best practices in infrastructure support Project deliverable: D2.3.1 Due date of deliverable: 30/04/2013 Actual submission date: 08/07/2013 Lead beneficiary: MTA SZTAKI Workpackage: WP2 - Supporting infrastructure Dissemination Level: PU (Public) Version: 6.0 (FINAL) IDGF-SP is supported by the FP7 Capacities Programme under contract nr RI-312297. D2.3.1 – Report on best practices in infrastructure support Copyright (c) 2013. Members of IDGF-SP consortium, see http://idgf-sp.eu/partners for details on the copyright holders. You are permitted to copy and distribute verbatim copies of this document containing this copyright notice but modifying this document is not allowed. You are permitted to copy this document in whole or in part into other documents if you attach the following reference to the copied elements: ‘Copyright (c) 2013. Members of IDGF-SP consortium - http://idgf-sp.eu’. The commercial use of any information contained in this document may require a license from the proprietor of that information. The IDGF-SP consortium members do not warrant that the information contained in the deliverable is capable of use, or that use of the information is free from risk, and accept no liability for loss or damage suffered by any person and organisation using this information. WP2 Copyright (c) 2013. Members of IDGF-SP consortium - http://idgf-sp.eu 2/52 D2.3.1 – Report on best practices in infrastructure support 1 Table of Contents 1 Table of Contents ............................................................................................................................ 3 2 Status and Change History .............................................................................................................
    [Show full text]