Distributed computing

Difference Between Grid Computing and Distributed Computing Definition of Distributed Computing Distributed Computing is an environment in which a group of independent and geographically dispersed computer systems take part to solve a complex problem, each by solving a part of solution and then combining the result from all computers. These systems are loosely coupled systems coordinately working for a common goal. It can be defined as A computing system in which services are provided by a pool of computers collaborating over a network .A computing environment that may involve computers of differing architectures and data representation formats that share data and system resources. Definition of Grid Computing The Basic idea between Grid Computing is to utilize the ideal CPU cycles and storage of million of computer systems across a worldwide network function as a flexible, pervasive, and inexpensive accessible pool that could be harnessed by anyone who needs it, similar to the way power companies and their users share the electrical grid. 1. 2.

Zooniverse (citizen science project) Zooniverse is a citizen science web portal owned and operated by the Citizen Science Alliance. The organization grew from the original Galaxy Zoo project and now hosts dozens of projects which allow volunteers to participate in scientific research. Unlike many early internet-based citizen science projects (such as SETI@home) which used spare computer processing power to analyse data, known as volunteer computing, Zooniverse projects require the active participation of human volunteers to complete research tasks. Projects have been drawn from disciplines including astronomy, ecology, cell biology, humanities, and climate science.[3] Active projects currently include: According to the Zooniverse site, these projects are now retired:

Ian Clarke (computer scientist) Ian Clarke (born 16 February 1977) is the original designer and lead developer of Freenet. Clarke grew up in Navan, County Meath, Ireland.[2] Clarke was educated at Dundalk Grammar School and while there twice came first in the Senior Chemical, Physical, and Mathematical section of the Young Scientist Exhibition. The first time, in 1993, was with a project entitled "The C Neural Network Construction Kit". The second time, the following year, was with a project entitled "Mapping Internal Variations in Translucency within a Translucent Object using Beams of Light".[3] In 1995 Clarke left Dundalk to study Computer Science and Artificial Intelligence at the University of Edinburgh, Scotland. In August 1999 Clarke began his first full-time job as a software developer in the Space Division of Logica plc, a London-based software consulting company. In September 2002, after leaving Uprizer, Clarke formed Cematics LLC to explore a variety of new ideas and opportunities.

SAMP --- Simple Application Messaging Protocol 1.4 About this Document This document contains the following main sections describing the SAMP protocol and how to use it. Section 2 covers the requirements, basic concepts and overall architecture of SAMP. Section 3 defines abstract (i.e. independent of language, platform and transport protocol) interfaces which clients and hubs must offer to participate in SAMP messaging, along with data types and encoding rules required to use them. Section 4 explains how the abstract API can be mapped to specific network operations to form an interoperable messaging system, and defines the "Standard Profile", based on XML-RPC, which gives a particular set of such mappings. Section 5 describes the use of the MType keys used to denote message semantics, and outlines an MType vocabulary. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in RFC 2119. 2 Architectural Overview

Apache ActiveMQ ™ -- Index YaCy : un moteur de recherche peer to peer sous licence libre pour remplacer Google Cet article a été publié il y a 3 ans 11 mois 4 jours, il est donc possible qu’il ne soit plus à jour. Les informations proposées sont donc peut-être expirées. C’est ma découverte du jour que je dois à Twitter et plus particulièrement à @glenux. En effet de YaCy, je n’avais encore jamais entendu parler bien qu’il existe depuis 2006. A la lecture de la présentation de YaCy, il y a de quoi être emballé. Ensuite, ce sont les caractéristiques techniques qui m’emballent : Une instance de YaCy peut stocker plus de 20 millions de documents.Partage d’index en peer to peer : YaCy implémente un système de partage d’index s’apparentant à un mécanisme de peer to peer (P2P). YaCy se décompose en quatre modules : un web crawler (le processus qui parcourt les pages web à indexer), un moteur d’indexation, une base de données et une interface utilisateur. Concernant la base de données embarquée, elle est spécifique à YaCy et utilise une structure de type AVL-Trees.

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Stellarium RabbitMQ - Messaging that just works Folding@home Distributed computing project simulating protein folding Folding@home (FAH or F@h) is a distributed computing project aimed to help scientists develop new therapeutics for a variety of diseases by the means of simulating protein dynamics. This includes the process of protein folding and the movements of proteins, and is reliant on simulations run on volunteers' personal computers.[5] Folding@home is currently based at the University of Pennsylvania and led by Greg Bowman, a former student of Vijay Pande.[6] The project utilizes graphics processing units (GPUs), central processing units (CPUs), and ARM processors like those on the Raspberry Pi for distributed computing and scientific research. Folding@home is one of the world's fastest computing systems. Background[edit] Examples of application in biomedical research[edit] Alzheimer's disease[edit] Alzheimer's disease is linked to the aggregation of amyloid beta protein fragments in the brain (right). Huntington's disease[edit] Cancer[edit]

Animated SVG Icons with Snap.svg Using SVGs on websites is becoming more and more easy with great libraries like Snap.svg. Today we want to explore what we can do with it and animate some SVG icons as a practical example. View demo Download source SVG has been one of the most underused technologies when it comes to web development. Despite it’s usefulness and powerful possibilities it’s still a mystery to many and when it comes to integrating it and using animations, many developers don’t know where to start. With great libraries like Snap.svg the use of SVG assets becomes more easy and today we’d like to explore how to animate SVG icons. You’ve surely seen some great examples of animated icons using CSS transitions and animations like the Navicon Transformicons by Bennett Feely which were explained in this excellent collaborative tutorial by Sara Soueidan. Please note that we are working with a modern JavaScript library for manipulating our SVGs. For each icon we want a special animation to happen.

Table - Java CoG Kit This page contains download information about the Java CoG Kit. We strongly recommend that you inspect the Instalation Guide. The full binary distribution of the Java CoG Kit including JGlobus can be downloaded from [tar.gz] [zip]. Details on the 4.1.5 release are available on the 4.1.5 Release page Additional information can be found if you follow to the Documentation page. Developers may be interested to directly work with the the newest source code from the SVN and compile the Binary themselves. The release table provides links to previous releases and to additional downloads such as a matlab interface to the Java CoG Kit. Legend:: n/a = not applicable or not available simply get it from CVS as discussed in the Instalation Guide

GPUGRID.net GPUGRID is a distributed computing project hosted by Pompeu Fabra University and running on the Berkeley Open Infrastructure for Network Computing (BOINC) software platform. It performs full-atom molecular biology simulations that are designed to run on Nvidia's CUDA-compatible graphics processing units. Former support for PS3s[edit] See also[edit] List of distributed computing projects References[edit] Further reading[edit] External links[edit]

Make the Type System Do the Work - Nathan Wong - Thinking in Code I wrote this post February 2012 and somehow never hit publish. So here it goes, two years later, to kick off February 2014. Declaring types and being restricted by the type system is often cited as a negative aspect of C++. I think this is an unfair assessment: a type system can make a programmer’s life considerably easier if it’s embraced instead of fought, as we’re seeing with the rise in popularity of Haskell. But C++, despite all its warts, has a pretty formidable type system of its own. The object-oriented paradigm is commonly taught with the “Dog is-a Mammal” architectural mentality where your classes are supposed to mirror real life objects and act accordingly. Specifically, we’re going to focus on the conversion of data from one form to another. A simple example that demonstrates the importance of dimensional consistency is temperature conversions. OK, it works. Instead, we should rely on the type system of the language to enforce this. Coordinates Further Reading