BOINC: a Platform for Volunteer Computing
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BIOINFORMATICS APPLICATIONS NOTE Doi:10.1093/Bioinformatics/Btq011
Vol. 26 no. 5 2010, pages 705–707 BIOINFORMATICS APPLICATIONS NOTE doi:10.1093/bioinformatics/btq011 Databases and ontologies Advance Access publication January 19, 2010 ProteinWorldDB: querying radical pairwise alignments among protein sets from complete genomes Thomas Dan Otto1,2,∗, Marcos Catanho1, Cristian Tristão3, Márcia Bezerra3, Renan Mathias Fernandes4, Guilherme Steinberger Elias4, Alexandre Capeletto Scaglia4, Bill Bovermann5, Viktors Berstis5, Sergio Lifschitz3, Antonio Basílio de Miranda1 and Wim Degrave1 1Laboratório de Genômica Funcional e Bioinformática, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil, 2Pathogen Genomics, Wellcome Trust Genome Campus, Hinxton, UK, 3Departamento de Informática, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, 4IBM Brasil, Hortolândia, São Paulo, Brazil and 5IBM, Austin, TX, USA Associate Editor: Alfonso Valencia ABSTRACT nomenclature or might have no value when inferred from previous Motivation: Many analyses in modern biological research are incorrectly annotated sequences. Hence, secondary databases based on comparisons between biological sequences, resulting such as Swiss-Prot (http://www.expasy.ch/sprot/), PFAM (http:// in functional, evolutionary and structural inferences. When large pfam.sanger.ac.uk) or KEGG (http://www.genome.ad.jp/kegg), to numbers of sequences are compared, heuristics are often used mention only a few, have been implemented to analyze specific resulting in a certain lack of accuracy. In order to improve functional aspects and to improve the annotation procedures and and validate results of such comparisons, we have performed results. radical all-against-all comparisons of 4 million protein sequences Dynamic programming algorithms, or a fast approximation, belonging to the RefSeq database, using an implementation of the have been successfully applied to biological sequence comparison Smith–Waterman algorithm. -
Volunteer Computing Different Grids for Different Needs
From the Web to the Grid How did the Grid start? • Name “Grid” chosen by analogy with electric power grid (Foster and Kesselman 1997) • Vision: plug-in computer for processing power just like plugging in toaster for electricity. • Concept has been around for decades (distributed computing, metacomputing) • Key difference with the Grid is to realise the vision on a global scale. From the Web to the Grid – 2007 HST 2011: Grids and Volunteer Computing Different Grids for different needs There is as yet no unified Grid, like there is a single web. Rather there are many Grids for many applications: • Enterprise Grids link together PCs within one company. • Volunteer computing links together public computers. • Scientific Grids link together major computing centres. • Latest trend federates national Grids into global Grid infrastructure. • High Energy Physics is a driving force for this. HST 2011: Grids and Volunteer Computing The LHC data challenge 1 Megabyte (1MB) • 40 million bunch collisions per second A digital photo 1 Gigabyte (1GB) = 1000MB • After filtering, ~100 collisions of 5GB = A DVD movie interest per second per detector 1 Terabyte (1TB) = 1000GB World annual book production • > 1 Megabyte of data per collision 1 Petabyte (1PB) recording rate > 1 Gigabyte/sec = 1000TB Annual production of one LHC experiment 10 • 10 collisions recorded each year 1 Exabyte (1EB) stored data ~15 Petabytes/year = 1000 PB 3EB = World annual information production …for more than 10 years HST 2011: Grids and Volunteer Computing Data Storage for the LHC Balloon (30 Km) • LHC data correspond to about 20 million CDs each year! CD stack with 1 year LHC data! (~ 20 Km) Concorde Where will the (15 Km) experiments store all of these data? Mt. -
Analysis and Predictions of DNA Sequence Transformations on Grids
Analysis and Predictions of DNA Sequence Transformations on Grids A Thesis Submitted for the Degree of Master of Science (Engineering) in the Faculty of Engineering By Yadnyesh R. Joshi Supercomputer Education and Research Centre INDIAN INSTITUTE OF SCIENCE BANGALORE – 560 012, INDIA August 2007 Acknowledgments First of all I would like to extend my sincere thanks to my research supervisor Dr. Sathish Vadhiyar for his constant guidance and support during the entire period of my post-graduation at IISc. He was always approachable, supportive and ready to help in any sort of problem. I am very thankful to him for being extremely patient and understanding about the silly mistakes that I had made. Under his guidance I learned to approach problems in an organized manner and set realistic goals for my research. I thank him for his extreme patience and excellent technical guidance in writing and presenting research. Finally, he was and continues to be my role model for his hard work and passion for research. I am also thankful to Dr. Nagasuma Chandra, Dr. Debnath Pal from S.E.R.C. and Dr. Narendra Dixit from Chemical Engineering department for their very useful and interesting insights into the biological domain of our research. I am also thankful to all the faculty of S.E.R.C. for always inspiring us with their motivational talks. I would like to mention the names of my colleagues Sandip, Sanjay, Rakhi, Sundari, Antoine and Roshan for making their technical and emotional support. Special thanks to vatyaa kya group members for the adventures and the routines inside and outside the institute. -
Distributed Computing with the Berkeley Open Infrastructure for Network Computing BOINC
Distributed Computing with the Berkeley Open Infrastructure for Network Computing BOINC Eric Myers -19 Update COVID8 July 2020 1 September 2010 Mid-Hudson Linux Users Group 2 How BOINC Works …for like 8 to 12 hrs! BOINC Client BOINC is the software BOINC Server Windows framework that makes Linux Mac OS this all work. Linux 50+ separate projects (& Solaris, AIX, HP-UX, etc…) 1 September 2010 Mid-Hudson Valley Linux Users Group 3 BOINC Dataflow 1 September 2010 Mid-Hudson Valley Linux Users Group 4 http://setiathome.berkeley.edu SETI@home SETI@home is ”paused” in 2020 http://einstein.phys.uwm.edu/ or http://einsteinathome.orG Einstein@Home 78 new pulsars detected by 2020 7 Rosetta@home 1 September 2010 Mid-Hudson Valley Linux Users Group 8 http://www.worldcommunitygrid.orG/ World CommunityAs of 2010 Grid Active The Clean Energy Project - Phase 2 Help Cure Muscular Dystrophy – Phase 2 Funded and operated by IBM Help Fight Childhood Cancer Help Conquer Cancer Human Proteome Folding - Phase 2 Completed FightAIDS@Home Nutritious Rice for the World Intermittent AfricanClimate@Home Discovering Dengue Drugs - Together - Phase 2 Help Cure Muscular Dystrophy Influenza Antiviral Drug Search Genome Comparison The Clean Energy Project Help Defeat Cancer Discovering Dengue Drugs - Together Human Proteome Folding 1 September 2010 Mid-Hudson Valley Linux Users Group 9 To Join: 1. Download BOINC 2. Run BOINC ManaGer 3. Tools -> Add Project 1 September 2010 Mid-Hudson Valley Linux Users Group 10 Call to Action! Use your spare cycles to help fight COVID-19 World Community Grid Rosetta@home OpenPandemics - COVID-19 8 July 2020 HVopen 11 Rules and Policies Run BOINC only on authorized computers Run BOINC only on computers that you own, or for which you have obtained the owner’s permission. -
Volunteer Computing and BOINC
Volunteer Computing and BOINC David P. Anderson Space Sciences Lab UC Berkeley MAGIC October 5, 2016 Scientific Volunteer Consumer computing computing electronics BOINC ● Middleware for volunteer computing – Open-source, NSF-funded development – Community-maintained ● Server: used by scientists to make “projects” ● Client: runs on consumer devices – “attach” to projects – fetches/runs jobs in background Example projects ● Climateprediction.net ● Rosetta@home ● Einstein@home ● IBM World Community Grid ● CERN Current volunteered resources ● 500,000 active devices – BOINC + Folding@home ● 2.3M CPU cores, 290K GPUs ● 93 PetaFLOPS ● 85% Windows, 7% Mac, 7% Linux Performance potential ● 1 billion desktop/laptop PCs – CPUs: 10 ExaFLOPS – GPUs: 1,000 ExaFLOPS ● 5 billion smartphones – CPUs: 20 ExaFLOPS – GPUs: 1,500 ExaFLOPS Realistic potential ● Study: 5-10% of people who learn about VC would participate ● Devices compute 60% of the time ● So if we can tell the world about VC, could get 100 ExaFLOPS Cost cost of 1 TFLOPS/year 4.5 4 3.5 3 2.5 2 cost ($M) 1.5 1 0.5 0 CPU cluster Amazon EC2 BOINC BOINC job model ● An app can have many versions ● Submit jobs to apps, not versions ● The BOINC scheduler decides what version(s) to use in response to a particular request Per-platform apps ● Windows/Intel, 32 and 64 bit ● Mac OS X ● Linux/Intel ● Linux/ARM (works for Android too) Other types of apps ● Multicore ● GPU apps – CUDA (Nvidia) – CAL (AMD) – OpenCL (Nvidia, AMD, Intel) VM apps ● App is VM image + executable ● BOINC client interfaces via “Vbox -
Laureate List 2011 3 27.Indd
THE LAUREATE THE COMPUTERWORLD HONORS PROGRAM | 2011 SYBASE CONGRATULATES OUR 2011 COMPUTERWORLD HONORS LAUREATES Bulgarian Electricity System Operator Cherry Creek School District Citizens Financial Group Everything Everywhere Limited JAGTAG Kodak Imaging Network Korea Ministry of Public Administration and Security (MOPAS) Matrix Systems and Solutions Medihelp Mobikash Afrika Congratulations Municipality of Aarhus 2011 Computerworld Honors Program New York State Division of Homeland Security and Emergency Laureates, Finalists, and Services — NY-ALERT 21st Century Achievement Award Recipients Oasis Medical Solutions Philippine Social Security System (SSS) Rafael Belloso Chacin University (URBE) Royal Netherlands Institute for Sea Research State of Maine Department of Health and Human Services Ready for what’s next. Swiss Medical Group, Argentina The desire to make a difference is the fi rst step that leads to success. Booz Allen Hamilton, a leading strategy and technology consulting fi rm, is proud Turkish Derivatives Exchange, Inc. (TurkDEX) to recognize the 2011 Computerworld Honors Program honorees. Thanks to your vision, commitment, and innovative use of IT, you’re making the world a better place. www.boozallen.com Copyright © 2011 Sybase, Inc. All rights reserved. Unpublished rights reserved under U.S. copyright laws. Sybase, and the Sybase logo, are trademarks of Sybase, Inc. or its subsidiaries. ® indicates registration in the United States of America. SAP, and the SAP logo, are the trademarks or registered trademarks of SAP AG in Germany and in several other countries. All other trademarks are the property of their respective owners. BA11-157_Computerworld Ad_052011Final.indd 1 5/20/11 8:32 AM . THE JOURNAL OF THE COMPUTERWORLD INFORMATION TECHNOLOGY AWARDS FOUNDATION . -
IBM's Contributions Towards Achieving the United Nations Sustainable
IBM’s contributions towards achieving the United Nations Sustainable Development Goals November 2018 2 Contents Introduction ............................................................................................................................................................ 3 Products, services and solutions ........................................................................................................................... 5 Blockchain .......................................................................................................................................................... 5 Watson IoT ......................................................................................................................................................... 6 Watson Health .................................................................................................................................................... 8 Workforce diversity and inclusion ........................................................................................................................ 10 Women in the workplace .................................................................................................................................. 10 Diversity constituencies ................................................................................................................................... 11 Accessibility and persons with disabilities ..................................................................................................... -
Dcp : Ar Tt Covid-19
Distributed Computing in a Pandemic: A Review of Technologies available for Tackling COVID-19 A Preprint Jamie J. Alnasir Department of Computing Imperial College London, UK [email protected] May 15, 2021 Abstract The current COVID-19 global pandemic caused by the SARS-CoV-2 betacoronavirus has resulted in over a million deaths and is having a grave socio-economic impact, hence there is an urgency to find solutions to key research challenges. Some important areas of focus are: vaccine development, designing or repurposing existing pharmacological agents for treatment by identifying druggable targets, predicting and diagnosing the disease, and tracking and reducing the spread. Much of this COVID-19 research depends on distributed computing. In this article, I review distributed architectures — various types of clusters, grids and clouds — that can be leveraged to performthese tasks at scale, at high-throughput,with a high degree of parallelism, and which can also be used to work collaboratively. High-performance computing (HPC) clusters, which aggregate their compute nodes using high- bandwidth networking and support a high-degree of inter-process communication, are ubiquitous across scientific research — they will be used to carry out much of this work. Several bigdata processing tasks used in reducing the spread of SARS-CoV-2 require high-throughput approaches, arXiv:2010.04700v3 [cs.DC] 18 May 2021 and a variety of tools, which Hadoop and Spark offer, even using commodity hardware. Extremely large-scale COVID-19 research has also utilised some of the world’s fastest supercom- puters, such as IBM’s SUMMIT — for ensemble docking high-throughput screening against SARS- CoV-2 targets for drug-repurposing,and high-throughputgeneanalysis — andSentinel, an XPE-Cray based system used to explore natural products. -
"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]. -
Analyzing Daily Computing Runtimes on the World Community Grid
https://doi.org/10.48009/3_iis_2020_289-297 Issues in Information Systems Volume 21, Issue 3, pp. 289-297, 2020 EXPLORING GRID COMPUTING & VOLUNTEER COMPUTING: ANALYZING DAILY COMPUTING RUNTIMES ON THE WORLD COMMUNITY GRID Kieran Raabe, Bloomsburg University of Pennsylvania, [email protected] Loreen M. Powell, Bloomsburg University of Pennsylvania, [email protected] ABSTRACT In the early 1990s, the concept of grid computing was little more than a simple comparison which stated that making computing power as accessible as electricity from a power grid. Today, grid computing is far more complex. Grid computing involves utilizing unused computing power from devices across the globe to run calculations and simulations and submit the results to move a project closer to its goal. Some projects, such as World Community Grid, work to achieve numerous goals, herein referred to as subprojects. The goal of this research is to explore grid computing and volunteer computing. Specifically, this research involved a daily collection of statistics on daily results returned to World Community Grid and daily computing runtimes for three subprojects named Africa Rainfall Project, Microbiome Immunity Project, and Help Stop TB. The data collection lasted four weeks and resulted in five graphs for each subproject being created with the collected data. Results revealed a correlation between daily results returned and daily runtimes, with each data point for results returned being slightly lower than the runtime data point from the same day. Keywords: Grid Computing, Volunteer Computing, BOINC, World Community Grid INTRODUCTION The concept of grid computing has existed since the early 1990s. Originally “a metaphor for making computer power as easy to access by the user as electricity from a power grid” (Dutton & Jeffreys, 2010). -
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. -
EDGES Project Meeting
International Desktop Grid Federation - Support Project Contract number: FP7-312297 Desktop Grids for e-Science Road Map Project deliverable: D5.5.1 Due date of deliverable: 2013-10-31 Actual submission date: 2013-12-27 Lead beneficiary: AlmereGrid Workpackage: WP5 Dissemination Level: PU Version: 1.2 (Final) IDGF-SP is supported by the FP7 Capacities Programme under contract nr FP7-312297. D5.5.1 – Desktop Grids for e-Science Road Map CopyriGht (c) 2013. MemBers of IDGF-SP consortium, see http://IDGF-SP.eu 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. WP3 © 2013. Members of IDGF-SP consortium - http://IDGF-SP.eu 2/8 D5.5.1 – Desktop Grids for e-Science Road Map Table of Contents 1 Status and ChanGe History .................................................................................................