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Grid computing is the use of widely distributed computerresources to reach a common goal. A computing grid can be thought of as a distributed system with non-interactive workloads that involve a large number of files. Grid computing is distinguished from conventional high-performance computing systems such as cluster computing in that grid computers have each node set to perform a different task/application. Grid computers also tend to be more heterogeneous and geographically dispersed (thus not physically coupled) than cluster computers.[1] Although a single grid can be dedicated to a particular application, commonly a grid is used for a variety of purposes. Grids are often constructed with general-purpose grid middleware software libraries. Grid sizes can be quite large.[2]
The terms distributed systems, and grid and cloud computing, actually refer to slightly different things. But the underlying concept is the same. This is based on delivering computing resources. Jan 16, 2019 Cloud computing training Program!! Grid: a grid is simply many computers which together might solve a given problem/crunch data. The fundamental difference between a grid and a cluster is that in a grid each node is relatively independent of others; problems are solved in a divide and conquer fashion.
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.
- 4Market segmentation of the grid computing market
- 6History
- 8Projects and applications
- 9See also
- 10References
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.
The size of a grid may vary from small—confined to a network of computer workstations within a corporation, for example—to large, public collaborations across many companies and networks. 'The notion of a confined grid may also be known as an intra-nodes cooperation whereas the notion of a larger, wider grid may thus refer to an inter-nodes cooperation'.[4]
Grids are a form of distributed computing whereby a “super virtual computer” is composed of many networked loosely coupled computers acting together to perform very large tasks. This technology has been applied to computationally intensive scientific, mathematical, and academic problems through volunteer computing, and it is used in commercial enterprises for such diverse applications as drug discovery, economic forecasting, seismic analysis, and back office data processing in support for e-commerce and Web services.
Coordinating applications on Grids can be a complex task, especially when coordinating the flow of information across distributed computing resources. Grid workflow systems have been developed as a specialized form of a workflow management system designed specifically to compose and execute a series of computational or data manipulation steps, or a workflow, in the grid context.
Comparison of grids and conventional supercomputers[edit]
“Distributed” or “grid” computing in general is a special type of parallel computing that relies on complete computers (with onboard CPUs, storage, power supplies, network interfaces, etc.) connected to a network (private, public or the Internet) by a conventional network interface producing commodity hardware, compared to the lower efficiency of designing and constructing a small number of custom supercomputers. The primary performance disadvantage is that the various processors and local storage areas do not have high-speed connections. This arrangement is thus well-suited to applications in which multiple parallel computations can take place independently, without the need to communicate intermediate results between processors.[5] The high-end scalability of geographically dispersed grids is generally favorable, due to the low need for connectivity between nodes relative to the capacity of the public Internet.[citation needed]
There are also some differences in programming and MC. It can be costly and difficult to write programs that can run in the environment of a supercomputer, which may have a custom operating system, or require the program to address concurrency issues. If a problem can be adequately parallelized, a “thin” layer of “grid” infrastructure can allow conventional, standalone programs, given a different part of the same problem, to run on multiple machines. This makes it possible to write and debug on a single conventional machine and eliminates complications due to multiple instances of the same program running in the same shared memory and storage space at the same time.
Design considerations and variations[edit]
One feature of distributed grids is that they can be formed from computing resources belonging to one or more multiple individuals or organizations (known as multiple administrative domains). This can facilitate commercial transactions, as in utility computing, or make it easier to assemble volunteer computing networks.
One disadvantage of this feature is that the computers which are actually performing the calculations might not be entirely trustworthy. The designers of the system must thus introduce measures to prevent malfunctions or malicious participants from producing false, misleading, or erroneous results, and from using the system as an attack vector. This often involves assigning work randomly to different nodes (presumably with different owners) and checking that at least two different nodes report the same answer for a given work unit. Discrepancies would identify malfunctioning and malicious nodes. However, due to the lack of central control over the hardware, there is no way to guarantee that nodes will not drop out of the network at random times. Some nodes (like laptops or dial-up Internet customers) may also be available for computation but not network communications for unpredictable periods. These variations can be accommodated by assigning large work units (thus reducing the need for continuous network connectivity) and reassigning work units when a given node fails to report its results in expected time.
Another set of what could be termed social compatibility issues in the early days of grid computing related to the goals of grid developers to carry their innovation beyond the original field of high-performance computing and across disciplinary boundaries into new fields, like that of high-energy physics.[6]
The impacts of trust and availability on performance and development difficulty can influence the choice of whether to deploy onto a dedicated cluster, to idle machines internal to the developing organization, or to an open external network of volunteers or contractors. In many cases, the participating nodes must trust the central system not to abuse the access that is being granted, by interfering with the operation of other programs, mangling stored information, transmitting private data, or creating new security holes. Other systems employ measures to reduce the amount of trust “client” nodes must place in the central system such as placing applications in virtual machines.
Public systems or those crossing administrative domains (including different departments in the same organization) often result in the need to run on heterogeneous systems, using different operating systems and hardware architectures. With many languages, there is a trade-off between investment in software development and the number of platforms that can be supported (and thus the size of the resulting network). Cross-platform languages can reduce the need to make this tradeoff, though potentially at the expense of high performance on any given node (due to run-time interpretation or lack of optimization for the particular platform). Various middleware projects have created generic infrastructure to allow diverse scientific and commercial projects to harness a particular associated grid or for the purpose of setting up new grids. BOINC is a common one for various academic projects seeking public volunteers; more are listed at the end of the article.
In fact, the middleware can be seen as a layer between the hardware and the software. On top of the middleware, a number of technical areas have to be considered, and these may or may not be middleware independent. Example areas include SLA management, Trust, and Security, Virtual organization management, License Management, Portals and Data Management. These technical areas may be taken care of in a commercial solution, though the cutting edge of each area is often found within specific research projects examining the field.
Market segmentation of the grid computing market[edit]
For the segmentation of the grid computing market, two perspectives need to be considered: the provider side and the user side:
The provider side[edit]
The overall grid market comprises several specific markets. These are the grid middleware market, the market for grid-enabled applications, the utility computing market, and the software-as-a-service (SaaS) market.
Grid middleware is a specific software product, which enables the sharing of heterogeneous resources, and Virtual Organizations. It is installed and integrated into the existing infrastructure of the involved company or companies and provides a special layer placed among the heterogeneous infrastructure and the specific user applications. Major grid middlewares are Globus Toolkit, gLite, and UNICORE.
Utility computing is referred to as the provision of grid computing and applications as service either as an open grid utility or as a hosting solution for one organization or a VO. Major players in the utility computing market are Sun Microsystems, IBM, and HP.
Grid-enabled applications are specific software applications that can utilize grid infrastructure. This is made possible by the use of grid middleware, as pointed out above.
Software as a service (SaaS) is “software that is owned, delivered and managed remotely by one or more providers.” (Gartner 2007) Additionally, SaaS applications are based on a single set of common code and data definitions. They are consumed in a one-to-many model, and SaaS uses a Pay As You Go (PAYG) model or a subscription model that is based on usage. Providers of SaaS do not necessarily own the computing resources themselves, which are required to run their SaaS. Therefore, SaaS providers may draw upon the utility computing market. The utility computing market provides computing resources for SaaS providers.
The user side[edit]
For companies on the demand or user side of the grid computing market, the different segments have significant implications for their IT deployment strategy. The IT deployment strategy as well as the type of IT investments made are relevant aspects for potential grid users and play an important role for grid adoption.
CPU scavenging[edit]
CPU-scavenging, cycle-scavenging, or shared computing creates a “grid” from the unused resources in a network of participants (whether worldwide or internal to an organization). Typically this technique uses a desktop computer instruction cycles that would otherwise be wasted at night, during lunch, or even in the scattered seconds throughout the day when the computer is waiting for user input on relatively fast devices. In practice, participating computers also donate some supporting amount of disk storage space, RAM, and network bandwidth, in addition to raw CPU power.[citation needed]
Many volunteer computing projects, such as BOINC, use the CPU scavenging model. Since nodes are likely to go 'offline' from time to time, as their owners use their resources for their primary purpose, this model must be designed to handle such contingencies.
Creating an Opportunistic Environment is another implementation of CPU-scavenging where special workload management system harvests the idle desktop computers for compute-intensive jobs, it also refers as Enterprise Desktop Grid (EDG). For instance, HTCondor[7] the open-source high-throughput computing software framework for coarse-grained distributed rationalization of computationally intensive tasks can be configured to only use desktop machines where the keyboard and mouse are idle to effectively harness wasted CPU power from otherwise idle desktop workstations. Like other full-featured batch systems, HTCondor provides a job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. It can be used to manage workload on a dedicated cluster of computers as well or it can seamlessly integrate both dedicated resources (rack-mounted clusters) and non-dedicated desktop machines (cycle scavenging) into one computing environment.
History[edit]
The term grid computing originated in the early 1990s as a metaphor for making computer power as easy to access as an electric power grid. The power grid metaphor for accessible computing quickly became canonical when Ian Foster and Carl Kesselman published their seminal work, 'The Grid: Blueprint for a new computing infrastructure' (1999). This was preceded by decades by the metaphor of utility computing (1961): computing as a public utility, analogous to the phone system.[8][9]
CPU scavenging and volunteer computing were popularized beginning in 1997 by distributed.net and later in 1999 by SETI@home to harness the power of networked PCs worldwide, in order to solve CPU-intensive research problems.[10][11]
The ideas of the grid (including those from distributed computing, object-oriented programming, and Web services) were brought together by Ian Foster and Steve Tuecke of the University of Chicago, and Carl Kesselman of the University of Southern California's Information Sciences Institute. The trio, who led the effort to create the Globus Toolkit, is widely regarded as the 'fathers of the grid'.[12] The toolkit incorporates not just computation management but also storage management, security provisioning, data movement, monitoring, and a toolkit for developing additional services based on the same infrastructure, including agreement negotiation, notification mechanisms, trigger services, and information aggregation. While the Globus Toolkit remains the de facto standard for building grid solutions, a number of other tools have been built that answer some subset of services needed to create an enterprise or global grid.[13]
In 2007 the term cloud computing came into popularity, which is conceptually similar to the canonical Foster definition of grid computing (in terms of computing resources being consumed as electricity is from the power grid) and earlier utility computing. Indeed, grid computing is often (but not always) associated with the delivery of cloud computing systems as exemplified by the AppLogic system from 3tera.[citation needed]
Progress[edit]
In November 2006, Seidel received the Sidney Fernbach Award at the Supercomputing Conference in Tampa, Florida.[14] 'For outstanding contributions to the development of software for HPC and Grid computing to enable the collaborative numerical investigation of complex problems in physics; in particular, modeling black hole collisions.'[15] This award, which is one of the highest honors in computing, was awarded for his achievements in numerical relativity.
Fastest virtual supercomputers[edit]
- As of February 2018, BOINC – 22 PFLOPS.[16]
- As of October 2016, Folding@home – 101 x86-equivalent PFLOPS.[17]
- As of February 2018, Einstein@Home – 3.489 PFLOPS.[18]
- As of February 2018, SETI@Home – 0.890 PFLOPS.[19]
- As of February 2018, MilkyWay@Home – 0.941 PFLOPS.[20]
- As of March 2019, GIMPS – 0.558 PFLOPS.[21]
Also, as of March 2019, the Bitcoin Network had a measured computing power equivalent to over 80,000,000 PFLOPS (Floating-point Operations Per Second).[22] This measurement reflects the number of FLOPS required to equal the hash output of the Bitcoin network rather than its capacity for general floating-point arithmetic operations, since the elements of the Bitcoin network perform only the specific cryptographic hash computation required by the Bitcoin protocol.
Projects and applications[edit]
Grid computing offers a way to solve Grand Challenge problems such as protein folding, financial modeling, earthquake simulation, and climate/weather modeling. Grids offer a way of using the information technology resources optimally inside an organization. They also provide a means for offering information technology as a utility for commercial and noncommercial clients, with those clients paying only for what they use, as with electricity or water.
As of October 2016, over 4 million machines running the open-source Berkeley Open Infrastructure for Network Computing (BOINC) platform are members of the World Community Grid.[16] One of the projects using BOINC is SETI@home, which was using more than 400,000 computers to achieve 0.828 TFLOPS as of October 2016. As of October 2016 Folding@home, which is not part of BOINC, achieved more than 101 x86-equivalent petaflops on over 110,000 machines.[17]
The European Union funded projects through the framework programmes of the European Commission. BEinGRID (Business Experiments in Grid) was a research project funded by the European Commission[23] as an Integrated Project under the Sixth Framework Programme (FP6) sponsorship program. Started on June 1, 2006, the project ran 42 months, until November 2009. The project was coordinated by Atos Origin. According to the project fact sheet, their mission is “to establish effective routes to foster the adoption of grid computing across the EU and to stimulate research into innovative business models using Grid technologies”. To extract best practice and common themes from the experimental implementations, two groups of consultants are analyzing a series of pilots, one technical, one business. The project is significant not only for its long duration but also for its budget, which at 24.8 million Euros, is the largest of any FP6 integrated project. Of this, 15.7 million is provided by the European Commission and the remainder by its 98 contributing partner companies. Since the end of the project, the results of BEinGRID have been taken up and carried forward by IT-Tude.com.
The Enabling Grids for E-sciencE project, based in the European Union and included sites in Asia and the United States, was a follow-up project to the European DataGrid (EDG) and evolved into the European Grid Infrastructure. This, along with the LHC Computing Grid[24] (LCG), was developed to support experiments using the CERNLarge Hadron Collider. A list of active sites participating within LCG can be found online[25] as can real time monitoring of the EGEE infrastructure.[26] The relevant software and documentation is also publicly accessible.[27] There is speculation that dedicated fiber optic links, such as those installed by CERN to address the LCG's
See also[edit]
Related concepts[edit]
Alliances and organizations[edit]
- Open Grid Forum (Formerly Global Grid Forum)
Production grids[edit]
International projects[edit]
Name | Region | Start | End |
---|---|---|---|
European Grid Infrastructure (EGI) | Europe | May 2010 | Dec 2014 |
Open Middleware Infrastructure Institute Europe (OMII-Europe) | Europe | May 2006 | May 2008 |
Enabling Grids for E-sciencE (EGEE, EGEE II and EGEE III) | Europe | March 2004 | April 2010 |
Grid enabled Remote Instrumentation with Distributed Control and Computation (GridCC) | Europe | September 2005 | September 2008 |
European Middleware Initiative (EMI) | Europe | May 2010 | active |
KnowARC | Europe | June 2006 | November 2009 |
Nordic Data Grid Facility | Scandinavia and Finland | June 2006 | December 2012 |
World Community Grid | Global | November 2004 | active |
XtreemOS | Europe | June 2006 | (May 2010) ext. to September 2010 |
OurGrid | Brazil | December 2004 | active |
National projects[edit]
- GridPP (UK)
- CNGrid (China)
- D-Grid (Germany)
- GARUDA (India)
- VECC (Calcutta, India)
- IsraGrid (Israel)
- INFN Grid (Italy)
- PL-Grid (Poland)
- National Grid Service (UK)
- Open Science Grid (USA)
- TeraGrid (USA)
Standards and APIs[edit]
Monitoring frameworks[edit]
References[edit]
- ^What is grid computing? - Gridcafe. E-sciencecity.org. Retrieved 2013-09-18.
- ^'Scale grid computing down to size'. NetworkWorld.com. 2003-01-27. Retrieved 2015-04-21.
- ^ ab'What is the Grid? A Three Point Checklist'(PDF).
- ^'Pervasive and Artificial Intelligence Group :: publications [Pervasive and Artificial Intelligence Research Group]'. Diuf.unifr.ch. May 18, 2009. Retrieved July 29, 2010.
- ^Computational problems - Gridcafe. E-sciencecity.org. Retrieved 2013-09-18.
- ^Kertcher, Zack; Coslor, Erica (2018-07-10). 'Boundary Objects and the Technical Culture Divide: Successful Practices for Voluntary Innovation Teams Crossing Scientific and Professional Fields'. Journal of Management Inquiry: 1056492618783875. doi:10.1177/1056492618783875. ISSN1056-4926.
- ^'HTCondor - Home'. research.cs.wisc.edu. Retrieved 14 March 2018.
- ^John McCarthy, speaking at the MIT Centennial in 1961
- ^Garfinkel, Simson (1999). Abelson, Hal (ed.). Architects of the Information Society, Thirty-Five Years of the Laboratory for Computer Science at MIT. MIT Press. ISBN978-0-262-07196-3.
- ^Anderson, David P; Cobb, Jeff; et al. (November 2002). 'SETI@home: an experiment in public-resource computing'. Communications of the ACM. 45 (11): 56–61. doi:10.1145/581571.581573.
- ^Nouman Durrani, Muhammad; Shamsi, Jawwad A. (March 2014). 'Volunteer computing: requirements, challenges, and solutions'. Journal of Network and Computer Applications. 39: 369–380. doi:10.1016/j.jnca.2013.07.006.
- ^'Father of the Grid'.
- ^Alaa, Riad; Ahmed, Hassan; Qusay, Hassan (31 March 2010). 'Design of SOA-based Grid Computing with Enterprise Service Bus'(PDF). INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences. 2 (1): 71–82. CiteSeerX10.1.1.208.827. doi:10.4156/aiss.vol2.issue1.6.
- ^'Edward Seidel 2006 Sidney Fernbach Award Recipient'. IEEE Computer Society Awards. IEEE Computer Society. Retrieved 14 October 2011.
- ^'Edward Seidel • IEEE Computer Society'. www.computer.org. Retrieved 14 March 2018.
- ^ ab'BOINCstats – BOINC combined credit overview'. Retrieved October 30, 2016.
- ^ abPande lab. 'Client Statistics by OS'. Folding@home. Stanford University. Retrieved October 30, 2016.
- ^'Einstein@Home Credit overview'. BOINC. Retrieved October 30, 2016.
- ^'SETI@Home Credit overview'. BOINC. Retrieved October 30, 2016.
- ^'MilkyWay@Home Credit overview'. BOINC. Retrieved October 30, 2016.
- ^'Internet PrimeNet Server Distributed Computing Technology for the Great Internet Mersenne Prime Search'. GIMPS. Retrieved March 12, 2019.
- ^bitcoinwatch.com. 'Bitcoin Network Statistics'. Bitcoin. Retrieved March 12, 2019.
- ^'beingrid.eu: Stromkosten Vergleiche -'. beingrid.eu: Stromkosten Vergleiche. Retrieved 14 March 2018.
- ^'Welcome to the Worldwide LHC Computing Grid - WLCG'. wlcg.web.cern.ch. Retrieved 14 March 2018.
- ^'GStat 2.0 – Summary View – GRID EGEE'. Goc.grid.sinica.edu.tw. Retrieved July 29, 2010.
- ^'Real Time Monitor'. Gridportal.hep.ph.ic.ac.uk. Archived from the original on December 16, 2009. Retrieved July 29, 2010.
- ^'LCG – Deployment'. Lcg.web.cern.ch. Retrieved July 29, 2010.
- ^'The Times & The Sunday Times'. thetimes.co.uk. Retrieved 14 March 2018.
- ^Athanaileas, Theodoros; et al. (2011). 'Exploiting grid technologies for the simulation of clinical trials: the paradigm of in silico radiation oncology'. SIMULATION: Transactions of the Society for Modeling and Simulation International. 87 (10): 893–910. doi:10.1177/0037549710375437.
- ^[1]Archived April 7, 2007, at the Wayback Machine
- ^P Plaszczak, R Wellner, Grid computing, 2005, Elsevier/Morgan Kaufmann, San Francisco
- ^IBM Solutions Grid for Business Partners: Helping IBM Business Partners to Grid-enable applications for the next phase of e-business on demand
- ^Structure of the Multics Supervisor. Multicians.org. Retrieved 2013-09-18.
- ^'A Gentle Introduction to Grid Computing and Technologies'(PDF). Retrieved May 6, 2005.
- ^'The Grid Café – The place for everybody to learn about grid computing'. CERN. Retrieved December 3, 2008.
Bibliography[edit]
- Buyya, Rajkumar; Kris Bubendorfer (2009). Market Oriented Grid and Utility Computing. Wiley. ISBN978-0-470-28768-2.
- Benedict, Shajulin; Vasudevan (2008). 'A Niched Pareto GA approach for scheduling scientific workflows in wireless Grids'. Journal of Computing and Information Technology. 16 (2): 101. doi:10.2498/cit.1001122.
- Davies, Antony (June 2004). 'Computational Intermediation and the Evolution of Computation as a Commodity'(PDF). Applied Economics. 36 (11): 1131. CiteSeerX10.1.1.506.6666. doi:10.1080/0003684042000247334.
- Foster, Ian; Carl Kesselman (1999). The Grid: Blueprint for a New Computing Infrastructure. Morgan Kaufmann Publishers. ISBN978-1-55860-475-9.
- Plaszczak, Pawel; Rich Wellner, Jr (2006). Grid Computing 'The Savvy Manager's Guide'. Morgan Kaufmann Publishers. ISBN978-0-12-742503-0.
- Berman, Fran; Anthony J. G. Hey; Geoffrey C. Fox (2003). Grid Computing: Making The Global Infrastructure a Reality. Wiley. ISBN978-0-470-85319-1.
- Li, Maozhen; Mark A. Baker (2005). The Grid: Core Technologies. Wiley. ISBN978-0-470-09417-4.
- Catlett, Charlie; Larry Smarr (June 1992). 'Metacomputing'. Communications of the ACM. 35 (6): 44–52. doi:10.1145/129888.129890.
- Smith, Roger (2005). 'Grid Computing: A Brief Technology Analysis'(PDF). CTO Network Library. Archived from the original(PDF) on 2012-02-18.
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- Berstis, Viktors. 'Fundamentals of Grid Computing'. IBM. Archived from the original on 2012-02-18.
- Elkhatib, Yehia (2011). Monitoring, Analysing and Predicting Network Performance in Grids(PDF) (Ph.D.). Lancaster University.
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- Francesco Lelli, Eric Frizziero, Michele Gulmini, Gaetano Maron, Salvatore Orlando, Andrea Petrucci and Silvano Squizzato. The many faces of the integration of instruments and the grid. International Journal of Web and Grid Services 2007 – Vol. 3, No.3 pp. 239 – 266 Electronic Edition
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Retrieved from 'https://en.wikipedia.org/w/index.php?title=Grid_computing&oldid=897789216'
In Clusters, all nodes are set to perform a same task,controlled and scheduled by some same application (OS)
In Grid Computing, nodes perform different tasks and maybe running diffrent applications independently.
So, a Grid may also consist of several Clusters.
I think the better answer is:
In cluster computing, a bunch of similar (or identical)computers are hooked up locally (in the same physical location,directly connected with very high speed connections) to operate asa single computer. The computers that make up the cluster cannot beoperated independently as separate computers. A cluster, as far asany software or other computer is concerned, looks like essentiallyone big computer.
In grid computing, the computers do not have to be in the samephysical location and can be operated independently. As far asother computers are concerned each computer on the grid is adistinct computer. Computers on a network have a program on themthat allows unused resources (usually processing time and memory)to be used by another computer on the network. The speed of theconnections between the computers on the grid are relatively slow(Ethernet speeds) compared to the speed of connections inside eachcomputer, so processing tasks are broken up into independent chunksand sent out to different computers on the grid. When a computer isdone with a chunk, it sends the results back to the server.
Roughly on a grid, a server log in to a bunch of computers (thegrid), send them data and a program to run, and runs the program onthose computers, which sends the data back to the server when itsdone.
In sum, a cluster is one large computer made up of small,similar computers, just as R.A.I.D. is one large hard disk made upof small hard disks. Whereas a grid is a bunch of computers thatmake their unused resources available to select computers (often asingle server) over a network.
What is the difference between distributed and cluster computing?
Distributed computing is computing done on computers connected by a network. Clusters are one type of distributed computing. MPPs are another. Grid computing is a third. Read More
Is grid computing an advanced computing?
'Distributed' or 'grid' computing in general is a special type of parallel computing, it is advanced in the means of using distributed computing. Read More
Compare between parallel computing grid computing and distributed computing?
Try checking out Gridipedia for a comprehensive overview of Grid computing: www.gridipedia.com Read More
When was Journal of Grid Computing created?
Journal of Grid Computing was created in 2003. Read More
What does the term grid computing refer to?
The term grid computing refers to collecting computer resources from multiple locations to reach common goals. A popular example of grid computing is the SETI project. You can get more information about grid computing at the Wikipedia. Read More
What is the grid computing?
Grid computing is a service for sharing computer power and data storage capacity over the Internet. The computers connected to the grid through network can be heterogeneous(that is the computers can have different hardware and OS) unlike cluster computing where it is mandatory that all computers should have same hardware and should run same operating system. Read More
Whats mean by grid computing?
Grid computing is a name given to a collection of distributed and parallel computing techniques that offer a whole range of advantages - for introductory material and case studies on Grid computing, check out Gridipedia Read More
Will you please send slides on grid computing?
try checking out Gridipedia if you need info on Grid computing Read More
What is the difference between Grid computing and peer-to-peer Computing?
Where can you get papers about grid computing?
What kind of people are drawn to grid computing?
People who need super-reliable computing to access to the Web Read More
What is the difference between cloud computing and grid computing?
Grid computing by definition is the collection of computer resources from multiple locations to reach a common goal. The grid can be thought of as a distributed system with non-interactive workloads that involves a large number of files. Cloud computing is a general terminology used for the delivery of hosted services over the Internet. Read More
What is GRIDS?
Is Internet necessary for grid computing?
What is malicious behavior in grid computing?
What the types of computing environments?
There are so many different types of computing environments today. The most common include cloud, grid, utility and distribute types of computing. Read More
How works grid computing?
What is the difference between Grid computing and high performance Computing?
I suggest you start by reading a good site on Grid computing. Personally I recommend Gridipedia. For example, as well as a good introduction, you can find read up on the business case behind it and see iti in action in the case study library they have: www.gridipedia.com Read More
What is the use of scentific computing in computer science?
Scientific computing play crucial rules in any field. In modern era, data is growing and new method arising for grid computing or telecommunication etc. They method needs computing power. Then scientific computing comes and play important rule in computer science. http://www.csd.cs.cmu.edu/research/areas/scicomp/ Read More
What is cloud computing system?
Cloud computing system is a type of computing system that relies on sharing computing resources rather than having local servers or personal devices to handle applications. The best thing about this system is...pay per use and another best thing about this system is............................................................ Cloud computing is comparable to grid computing, a type of computing where unused processing cycles of all computers in a network are harnesses to solve problems too intensive for any stand-alone machine. Read More
What is meaning of g in oracle 10g or 11g?
g stands for Grid. These versions introduced the use of grid computing techniques. Read More
What is meaning of g in oracle 10g?
Like MySQL , Oracle is also a database . Oracle has a number of versions like 9i, 10g, 11g etc. 'g' in the oracle 11g stands for grid computing. Read More
What do you mean by g in oracle 10g?
Oracle is a database just like MySQL. Oracle has a number of versions today like 9i, 11g, 12c etc . In oracle 11g , 'g' stands for grid computing. Read More
What is an explanation of the advancement of cloud computing?
Cloud Computing Advancements in Design, Implementation, and Technologies outlines advancements in the state-of-the-art, standards, and practices of cloud computing, in an effort to identify emerging trends that will ultimately define the future of the cloud. A valuable reference for academics and practitioners alike, this title covers topics such as virtualization technology, utility computing, cloud application services (SaaS), grid computing, and services computing. Read More
Where can i get papers on grid computing?
Just use an internet search engine; it will bring up many references from grid vendors and researchers. Read More
What does PGA mean in computing?
PGA Pin Grid Array is the socket that holds the CPU, there is also the LGA/ land grid array Read More
What is NorduGrid's motto?
NorduGrid's motto is 'Grid Solution for Wide Area Computing and Data Handling'. Read More
Full form of 10g in oracle?
the full form of 10g in oracle is g=grid computing Read More
What is BOINC manager?
The Berkeley Open Infrastructure for Network Computing (BOINC) is a non-commercial middleware system for volunteer and grid computing. You are probably referring to its management console. Read More
What is the future implementation of grid computing?
who knows? Some talk about a global grid where all services are provided à la cloud - others see numerous smaller, more business centric grids emerging. What ever the case, check out Gridipedia's library of case studies on grid computing which will show you how Grid is being used ruight now in everything from filmaking to pharmacy. Read More
Why is the new grid computing system at Advance America much easier to install manage and maintain than its old system-?
The new grid computing system at Advance America is much easier to install, manage ,and maintain than its old system because of its user-friendly interface. Read More
Differce between computing and ditrubuted computing?
Hi 1. Distributed Computing normally refers to managing or pooling the hundreds or thousands of computer systems which individually are more limited in their memory and processing power. On the other hand, grid computing has some extra characteristics. It is concerned to efficient utilization of a pool of heterogeneous systems with optimal workload management utilizing an enterprise's entire computational resources( servers, networks, storage, and information) acting together to create one or more large pools of… Read More
What are the applications of parallel processing?
In a nut shell. The most common applications of parallel computing/processing are solving extremly complex problems whithin the science and engineering communities e.g. ... grid computing and internet technology. Read More
Why is the new grid computing system at Advance America much easier to install manage and maintain than its old system?
The new grid computing system at Advance America is much easier to install,manage and maintain than its old system since it was upgraded and made to be customer friendly. Read More
What is the difference between distributed systems and grid services?
its complicated. Distributed computing is a term used to focus on methods and practices used to overcome challenges presented by operating in a distributed environment - heterogenity, latency, etc. Grid computing by it's nature is often distributed so it encompasses distributed computing. It is also based on parallel computing paradigms - where you split the computation between multiple processors to speed up the calculations. Grid technology is much bigger than either of these terms though… Read More
What has the author Ralf Gruber written?
Ralf Gruber has written: 'HPC@green IT' -- subject(s): Hochleistungsrechnen, Green-IT, Environmental aspects, High performance computing, Grid Computing, Betriebsmittelverwaltung, Information technology, Energieeffizienz Read More
What are advantages of grid computing?
It reduces research time from years to months, it is also a more cost effective technology. Read More
What is the meaning of g in oracle 11g?
G signifies 'Grid Computing'... With the release of Oracle 10g in 2003, Oracle changed the suffix in their previous release version; from 9i to 10g... 'I' stands for Internet...this was done as a marketing effort in order to show Oracle's move towards Grid Computing... Purely a marketing strategy... Read More
Why is windows xp good for distributed computing?
Windows XP is actually very poorly suited for most forms of distributed computing, except for grid computing where tasks can be performed asynchronously on uncoupled machines. Windows XP doesn't support more than four cores or two physical processors, making it unideal for large multithreaded tasks. No version has ever been released that would be able to effectively operate in a cluster, either. Linux, Mac OS X (with XGrid) or Windows HPC 2008 would be much… Read More
What is the difference between Clustered Systems and Distributed Systems?
clustered system: systems having many computers with shared storage and linked by a lan or network. distributed system: systems having many computers connected by a network and there is no shared storage. Distributed computing is computing done on computers connected by a network. Clusters are one type of distributed computing. MPPs are another. Grid computing is a third. Read More
What is the grid techonolgy?
Grid technology is a means of using parallel and distributed computing models in order to achieve high performance, flexability, cost effectiveness and efficiency from an IT system. A good collection of resources are available at Gridipedia Read More
How did gird computing help Advance America in breaking through the limitations that help it back from growth?
The grid computing helped Advance America in breaking through the limitations that help it back from growth by being easy to use and allow for flexibility in terms of use and management.Grid computing helped Advance America in breaking through the limitations that held it back from growth through presentation of a platform that made it possible to distribute applications and technology. Read More
What is an aggregation of geographically dispersed computing storage and network resources coordinated to deliver improved performance higher quality of service better utilization?
What is the difference between Oracle 9i and Oracle 10i?
storage is different as compared 9i with 10i.........10i uses grid computing...this has more data storage space Read More
What can do with grid computing?
we can able to reduce our working time and we can able to make system more faster and never allowing system to be in idle condition ,we can able to get answer in fraction of seconds Read More
What is distrubuted computing?
Distributed computing indicates a relationship among multiple, remotely operating computers simultaneously involved in solving computational problems or facilitating data processing methods. Business enterprises frequently employ distributed computing as a way to implement the various stages comprising a particular process at the most efficacious point within the computer network. For example, typical distributed computing events accommodating the three-step model includes processing of the user interface at the user's computer and effecting business processes at a remote… Read More
What is the meaning of i in oracle9i?
Oracle i means 'Internet', that means oracle manipulate data via internet. But next oracle comes with 'Grid Computing' and rename with 'g' Read More
Is there software that allows local area networked PCs to borrow CPU power or clock cycles from each other?
Yes - this is known as grid computing, where the idle time of a processor may be used to work on a piece of a large computing problem that is too big for a single system to solve. There are both commercial and freely available packages to harness several computers or networks together in a grid and use their available CPU cycles. Read More
High performance computing?
What is High Performance Computing? High performance computing -- or HPC -- is the practical application of the mighty 'supercomputer' and has been steadily developed since the 1960s to tackle complex and large scale computations. The Components Involved in High Performance Computing Technology A standard desktop computer usually contains a single processor, therefore leaving it stranded in the wake of a high performance computing system, which is a self-contained network with an entire system of… Read More
What is the difference between oracle 8i and 9i and 10g?
The 'i' and 'g' Versions Starting in 1999 with Version 8i, Oracle added the 'i' to the version name to reflect support for the Internet with its built-in Java Virtual Machine (JVM). Oracle 9i added more support for XML in 2001. In 2003, Oracle 10g was introduced with emphasis on the 'g' for grid computing, which enables clusters of low-cost, industry standard servers to be treated as a single unit. 10g is Oracle's grid computing… Read More