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Distributed computing is a field of computer science that studies distributed systems, defined as computer systems whose inter-communicating components are located on different networked computers. [1] [2] The components of a distributed system communicate and coordinate their actions by passing messages to
Distributed data processing. Distributed data processing [1] (DDP) [2] was the term that IBM used for the IBM 3790 (1975) and its successor, the IBM 8100 (1979). Datamation described the 3790 in March 1979 as "less than successful." [3] [4] Distributed data processing was used by IBM to refer to two environments: IMS DB/DC; CICS/DL/I [5] [6]
Distributed Processing Technology Corporation (DPT) was an American computer hardware company active from 1977 to 1999. Founded in Maitland, Florida , DPT was an early pioneer in computer storage technology, popularizing the use of disk caching in the 1980s and 1990s.
Stream processing is essentially a compromise, driven by a data-centric model that works very well for traditional DSP or GPU-type applications (such as image, video and digital signal processing) but less so for general purpose processing with more randomized data access (such as databases). By sacrificing some flexibility in the model, the ...
A distributed SQL database is a single relational database which replicates data across multiple servers. Distributed SQL databases are strongly consistent and most support consistency across racks, data centers, and wide area networks including cloud availability zones and cloud geographic zones .
A grid computing system that connects many personal computers over the Internet via inter-process network communication. In computer science, interprocess communication (IPC) is the sharing of data between running processes in a computer system.
Distributed Data Management Architecture (DDM) is IBM's open, published software architecture for creating, managing and accessing data on a remote computer. DDM was initially designed to support record-oriented files; it was extended to support hierarchical directories, stream-oriented files, queues, and system command processing; it was further extended to be the base of IBM's Distributed ...
Distributed Artificial Intelligence (DAI) is an approach to solving complex learning, planning, and decision-making problems.It is embarrassingly parallel, thus able to exploit large scale computation and spatial distribution of computing resources.