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:

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.

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]

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]

Grid computing The use of widely distributed computer resources to reach a common goal Grids are a form of distributed computing whereby a "super virtual computer" is composed of many networked loosely coupled computers acting together to perform large tasks. For certain applications, distributed or grid computing can be seen as a special type of parallel computing that relies on complete computers (with onboard CPUs, storage, power supplies, network interfaces, etc.) connected to a computer network (private or public) by a conventional network interface, such as Ethernet. This is in contrast to the traditional notion of a supercomputer, which has many processors connected by a local high-speed computer bus. Overview[edit] Grid computing combines computers from multiple administrative domains to reach a common goal,[3] to solve a single task, and may then disappear just as quickly. Comparison of grids and conventional supercomputers[edit] Design considerations and variations[edit] The provider side[edit]

Le portail de l'Alliance Francophone - Accueil Multicast In computer networking, multicast is the delivery of a message or information to a group of destination computers simultaneously in a single transmission from the source. Copies are automatically created in other network elements, such as routers, but only when the topology of the network requires it. At the Data Link Layer, multicast describes one-to-many distribution such as Ethernet multicast addressing, Asynchronous Transfer Mode (ATM) point-to-multipoint virtual circuits (P2MP) or Infiniband multicast. IP multicast[edit] IP multicast is a technique for one-to-many communication over an IP infrastructure in a network. The most common transport layer protocol to use multicast addressing is User Datagram Protocol (UDP). IP multicast is widely deployed in enterprises, commercial stock exchanges, and multimedia content delivery networks. Other multicast technologies[edit] Other multicast technologies not based on IP multicast are more widely used. See also[edit] References[edit]

Constellation Exactly 1week to "Space Race - Yuri's Night 2014: Hunting Comets!" team challenge on BoincStats Hello everyone, in exactly one week the "Space Race - Yuri's Night 2014: Hunting Comets!" team challenge on BoincStats will start. The challenge will support our Comet Trails simulation by the Dust Team of the Insitute of Space Systems (IRS) at University of Stuttgart. There are already 14 teams in for for the Yuri's Night challenge and we hope to see more of you participating there. This is our annual team challenge to honor Yuri Gagarin, first human in space, and our own birthday. Comet Trails: An IMEX application for predicting meteor storms at spacecraft or planets AerospaceResearch.net is happy to announce the next application running on the Constellation platform, the "IMEX Cometary trails". (click here for Youtube-video Dr. comet_trails_jupiter by aerospaceresearch.net on Flickr First Work-Units: Our first workunits are to compute streams for the Leonids and the October Draconids.