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Stream editing processes a file or files, in-place, without having to load the file(s) into a user interface. One example of such use is to do a search and replace on all the files in a directory, from the command line. On Unix and related systems based on the C language, a stream is a source or sink of data, usually individual bytes or characters.
A special case is the majority problem, which is to determine whether or not any value constitutes a majority of the stream. More formally, fix some positive constant c > 1, let the length of the stream be m, and let f i denote the frequency of value i in the stream. The frequent elements problem is to output the set { i | f i > m/c }. [13]
The above notwithstanding, systolic arrays are often offered as a classic example of MISD architecture in textbooks on parallel computing and in the engineering class. If the array is viewed from the outside as atomic it should perhaps be classified as SFMuDMeR = single function, multiple data, merged result(s). [3] [4] [5] [6]
Stream processing hardware can use scoreboarding, for example, to initiate a direct memory access (DMA) when dependencies become known. The elimination of manual DMA management reduces software complexity, and an associated elimination for hardware cached I/O, reduces the data area expanse that has to be involved with service by specialized ...
In computing, a sink, or data sink generally refers to the destination of data flow.. The word sink has multiple uses in computing. In software engineering, an event sink is a class or function that receives events from another object or function, while a sink can also refer to a node of a directed acyclic graph with no additional nodes leading out from it, among other uses.
In this system, classifications are based upon the number of concurrent instructions and data streams present in the computer architecture. According to Michael J. Flynn, SISD can have concurrent processing characteristics. Pipelined processors and superscalar processors are common examples found in most modern SISD computers. [2] [3]
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The main problem with this approach is accuracy: as the A-stream becomes more accurate and less speculative, the overall system runs slower [citation needed]. Furthermore, a large enough distance is needed between the A-stream and the R-stream so that cache misses generated by the A-stream do not slow down the R-stream.