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"Distributed" or "grid" computing in general is a special type of parallel computing, it is advanced in the means of using distributed computing.

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supercomputers allows both parallel and distributed computing

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Serial computing is executing a task on one computer. Distributed computing is executing a task on multiple computers at the same time.

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Parallel computing and distributed computing are ways of exploiting parallelism in computing to achieve higher performance. Multiple processing elements are used to solve a problem, either to have it done faster or to have a larger size problem been solved. To state simply, if the processing elements share the memory, it is called parallel computing, other wise it is called distributed computing. Some have opinion that distributed computing is a special form of parallel computing.

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HIGH AVAILABILITY provided by Fault Tolerant Computing Systems & Networks which might be geographically distributed and thus overcomes Single Point of Failurein mission critical applications is the main goal of Distributed Computing.

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Grid Computing and Distributed Systems

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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.

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Master of Engineering in Distributed Computing

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Sky Computing is an emerging computing model where resources from multiple clouds providers are leveraged to create large scale distributed infrastructures."

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Information systems using a mainframe are referred to as distributed because computing results must be distributed to users at various locations.

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Distributed computing involves multiple computers working together on a task, often across a network, while parallel computing uses multiple processors within a single computer to work on a task simultaneously. Distributed computing can be more flexible and scalable but may face challenges with communication and coordination between the computers. Parallel computing can be faster and more efficient for certain tasks but may be limited by the number of processors available. The choice between distributed and parallel computing depends on the specific requirements of the task at hand.

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Information systems using a mainframe are referred to as distributed because computing results must be distributed to users at various locations.

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In the most simple form = Parallel Computing is a method where several individual (autonomous) systems (CPU's) work in tandem to resolve a common computing workload.

Distributed Computing is where several dis-associated systems are working seperatly to resolve a multi-faceted computing workload.

An example of Parallel computing would be two servers that share the workload of routing mail, managing connections to an accounting system or database, solving a mathematical problem, ect...

Distributed Computing would be more like the SETI Program, where each client works a separate "chunk" of information, and returns the completed package to a centralized resource that's responsible for managing the overall workload.

If you think of ten men pulling on a rope to lift a load, that is parallel computing. If ten men have ten ropes and are lifting ten different loads from one place to consolidate at another place, that would be distributed computing.

In Parallel Computing all processors have access to a shared memory. In distributed computing, each processor has its own private memory

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Parallel computing involves breaking down a task into smaller parts and processing them simultaneously on multiple processors within the same system, while distributed computing involves spreading the task across multiple computers connected over a network to process it efficiently.

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Parallel computing involves breaking down a task into smaller parts that are processed simultaneously by multiple processors within the same system. Distributed computing, on the other hand, involves processing tasks across multiple interconnected systems, often geographically dispersed. The key difference lies in how the tasks are divided and executed, with parallel computing focusing on simultaneous processing within a single system and distributed computing focusing on processing across multiple systems.

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HIGH AVAILABILITY provided by Fault Tolerant Computing Systems & Networks which might be geographically distributed and thus overcomes Single Point of Failurein mission critical applications is the main goal of Distributed Computing.

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Distributed computing is when a network of computers are used collectively to perform the same task while sharing the workload. Mobile computing, you pick up your laptop and head off on holiday!

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In other fields tightly coupled means that two entities are closely associated. Probably, in Distributed Computing, it means that a module in the distributed architecture is closely related to the other modules. Therefore, this module only can be replaced by a very similar one.

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hi,

go to porivo.com

the Gomez peer program pays $5 per month per computer.

Troy

Thomaswarner - That isn't distributed computing, but it works in a similar way. It's more like distributed website testing.

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Installation of software, configuration of an IS or connecting any ISs to a distributed computing environment with prior approval.

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What is the difference between parallel computing and distributing computing?

In the most simple form = Parallel Computing is a method where several individual (autonomous) systems (CPU's) work in tandem to resolve a common computing workload.

Distributed Computing is where several dis-associated systems are working seperatly to resolve a multi-faceted computing workload.

An example of Parallel computing would be two servers that share the workload of routing mail, managing connections to an accounting system or database, solving a mathematical problem, ect...

Distributed Computing would be more like the SETI Program, where each client works a seperate "chunk" of information, and returns the completed package to a centralized resource that's responsible for managing the overall workload.

If you think of ten men pulling on a rope to lift a load, that is parallel computing. If ten men have ten ropes and are lifting ten different loads from one place to consolidate at another place, that would be distributed computing.

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Cloud computing refers to distributed computing on an internet network. Leading companies include Google, Amazon, Oracle and others. Corresponding states include California, Washington and more.

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gangalia:is a distributed monitering system for high performance computing systems such as clusters and grids

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Ricardo Couto Antunes da Rocha has written:

'Context management for distributed and dynamic context-aware computing' -- subject(s): Electronic data processing, Distributed processing, Context-aware computing

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Distributed computing involves breaking down tasks and distributing them across multiple nodes or processors that work independently on different parts of the task. Parallel computing, on the other hand, involves dividing a task into smaller subtasks that are processed simultaneously by multiple nodes or processors working together.

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Parallel computing involves breaking down a task into smaller parts that can be processed simultaneously by multiple processors within the same machine. Distributed computing, on the other hand, involves dividing a task among multiple computers connected over a network, with each computer working on a different part of the task.

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Dejian Zhou has written:

'Processor assignment problem in distributed computing'

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Distributed Software engineering is combination of distributed system engineering and distributed system architecture

For more detail you need to go through the following topics

1)Distributed systems issues

2)Client-server computing

3)Architectural patterns for distributed systems

4)Software as a service

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Parallel computing involves breaking down a task into smaller parts that are executed simultaneously on multiple processors within the same system. Distributed computing, on the other hand, involves dividing a task among multiple independent computers connected through a network.

The key difference lies in how the tasks are divided and executed. In parallel computing, all processors have access to shared memory, allowing for faster communication and coordination. In distributed computing, communication between computers is slower due to network latency.

This difference impacts performance and scalability. Parallel computing can achieve higher performance for tasks that can be divided efficiently among processors, but it may face limitations in scalability due to the finite number of processors available. Distributed computing, on the other hand, can scale to a larger number of computers, but may face challenges in coordinating tasks and managing communication overhead.

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C.J Chun has written:

'Clie nt/server computing in distributed environment'

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Distributed Software engineering is combination of distributed system engineering and distributed system architecture

For more detail you need to go through the following topics

1)Distributed systems issues

2)Client-server computing

3)Architectural patterns for distributed systems

4)Software as a service

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For projects like Folding@home, there isn't too much of a difference, although Linux always seems to have a slight edge.

If you want to run a distributed computing network at home, there are specialist Linux OSes such as Beowulf which take a lot of the pain out of the process

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well the main difference is that in a parallel system there is multiple computing units (cpu) working in one node(they share memory ,attached devices , storage...) to accomplish a computing goal

in a clustered there is multiple nodes each has its own resources running its own copy of os (usually connected via lan) to accomplish a computing goal

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A computer network gives access to files on separate computer, while distributed computing is giving access to the CPU power of a separate computer

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Dana Petcu has written:

'European research activities in cloud computing' -- subject(s): Electronic data processing, Cloud computing, Distributed processing, Research

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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 computer. Finally, processing as well as database access is completed within a separate computer capable of providing consolidated access for numerous business processes. This is also referred to as the "client/server" model of distributed computing.

One of the first instances of using distributing computing methods was enacted by the group distributed.net, in which users were able to break a cryptographic code. Early development of streamlining the communication of multiple computers through a single network in pursuit of a common goal has now evolved into the advanced field of distributed computing that permits finalization of computation problems in real time.

Other terms for distributed computing include parallel computing and concurrent computing, with slight variations in the meaning of these terms. Distributed computing, for example, involves processors with individual memories that are private and only shared when users deliberately exchange messages among processors. Alternately, parallel computing may involve users being able to access shared memory without needing to intentionally exchange data.

Fundamental properties characterizing a distributed computing system include:

  • It must be able to sustain failures in remote computers
  • It contains structural components, such as network latency and topology, that is not detected prior to creating the system
  • Individual computers comprising the system have incomplete and limited views of the distributing computing system. In other words, each remote computer may have knowledge of only one aspect of the total input

Commonly used distributed computing applications and systems are cellular, internet and telephone networks; routing algorithms; peer-to-peer networks; virtual communities; multiplayer games; airline reservation, aircraft control and banking systems and grid/cluster computing.

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It is a class of algorithms that are fine-tuned towards making the best out of a distributed computing ( similar to cloud computing ) environment. A very good example of such an algorithm is MapReduce (see wikipedia).

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Parallel and distributed computing can improve performance and scalability by allowing tasks to be divided and processed simultaneously across multiple processors or machines. This can lead to faster execution times and increased efficiency in handling large amounts of data or complex computations. Additionally, parallel and distributed computing can enhance fault tolerance and reliability by distributing workloads across multiple nodes, reducing the risk of system failures and improving overall system resilience.

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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 computer. Finally, processing as well as database access is completed within a separate computer capable of providing consolidated access for numerous business processes. This is also referred to as the "client/server" model of distributed computing.

One of the first instances of using distributing computing methods was enacted by the group distributed.net, in which users were able to break a cryptographic code. Early development of streamlining the communication of multiple computers through a single network in pursuit of a common goal has now evolved into the advanced field of distributed computing that permits finalization of computation problems in real time.

Other terms for distributed computing include parallel computing and concurrent computing, with slight variations in the meaning of these terms. Distributed computing, for example, involves processors with individual memories that are private and only shared when users deliberately exchange messages among processors. Alternately, parallel computing may involve users being able to access shared memory without needing to intentionally exchange data.

Fundamental properties characterizing a distributed computing system include:

  • It must be able to sustain failures in remote computers
  • It contains structural components, such as network latency and topology, that is not detected prior to creating the system
  • Individual computers comprising the system have incomplete and limited views of the distributing computing system. In other words, each remote computer may have knowledge of only one aspect of the total input

Commonly used distributed computing applications and systems are cellular, internet and telephone networks; routing algorithms; peer-to-peer networks; virtual communities; multiplayer games; airline reservation, aircraft control and banking systems and grid/cluster computing.

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A distributed computing system requires each machine attached to the network to has specific software allowing them to talk to each other. A distributed virtual systems allows the machines on a network to talk to each other without the use of central software.

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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 as it also entails resource sharing, security systems, SLA management - as can be seen at www.Gridipedia.eu.

Grid services are used within the Grid to carry out one function - processing, storage, instrumentsation, a softwarre process etc. for more info check oput Gridipedia¡s glossary - Grid Dic

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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.

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Dermot Kelly has written:

'The implementation of high level group structures for distributed services' -- subject(s): Electronic data processing, Distributed processing, Client/server computing

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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 computing resources. There is no limitation of users, departments or originations in grid computing.

2. Grid computing is focused on the ability to support computation across multiple administrative domains that sets it apart from traditional distributed computing. Grids offer a way of using the information technology resources optimally inside an organization involving virtualization of computing resources. Its concept of support for multiple administrative policies and security authentication and authorization mechanisms enables it to be distributed over a local, metropolitan, or wide-area network.

Hope this helps , Best wishes :)

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Distributed computing is used to efficiently process large amounts of data by breaking the workload into smaller tasks that can be handled simultaneously by multiple computers. This allows for faster processing and better utilization of resources, resulting in quicker and more efficient data processing.

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