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Parallel computing may be seen as a particularly tightly coupled form of distributed computing, [26] and distributed computing may be seen as a loosely coupled form of parallel computing. [13] Nevertheless, it is possible to roughly classify concurrent systems as "parallel" or "distributed" using the following criteria:
In computing, a distributed file system (DFS) or network file system is any file system that allows access from multiple hosts to files shared via a computer network. This makes it possible for multiple users on multiple machines to share files and storage resources.
Grid computing is the most distributed form of parallel computing. It makes use of computers communicating over the Internet to work on a given problem. Because of the low bandwidth and extremely high latency available on the Internet, distributed computing typically deals only with embarrassingly parallel problems.
One approach is grid computing, where the processing power of many computers in distributed, diverse administrative domains is opportunistically used whenever a computer is available. [1] An example is BOINC , a volunteer-based , opportunistic grid system, whereby the grid provides power only on a best effort basis.
Modern data centers must support large, heterogenous environments, consisting of large numbers of computers of varying capacities. Cloud computing coordinates the operation of all such systems, with techniques such as data center networking (DCN), the MapReduce framework, which supports data-intensive computing applications in parallel and distributed systems, and virtualization techniques ...
Cloud bursting is an application deployment model in which an application runs in a private cloud or data center and "bursts" to a public cloud when the demand for computing capacity increases. A primary advantage of cloud bursting and a hybrid cloud model is that an organization pays for extra compute resources only when they are needed. [ 68 ]
Distributed systems, parallel computing, and high-performance computing; Database systems, web applications, and cloud computing; Related concepts
"Embarrassingly" is used here to refer to parallelization problems which are "embarrassingly easy". [4] The term may imply embarrassment on the part of developers or compilers: "Because so many important problems remain unsolved mainly due to their intrinsic computational complexity, it would be embarrassing not to develop parallel implementations of polynomial homotopy continuation methods."
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