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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]
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 ...
Examples of distributed memory (multiple computers) include MPP (massively parallel processors), COW (clusters of workstations) and NUMA (non-uniform memory access). The former is complex and expensive: Many super-computers coupled by broad-band networks. Examples include hypercube and mesh interconnections.
In the aircraft example, the observer on the ground will observe unsteady flow, and the observers in the aircraft will observe steady flow, with constant streamlines. When possible, fluid dynamicists try to find a reference frame in which the flow is steady, so that they can use experimental methods of creating streaklines to identify the ...
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.
The problem to determine all positive integers such that the concatenation of and in base uses at most distinct characters for and fixed [citation needed] and many other problems in the coding theory are also the unsolved problems in mathematics.
The streamline upwind Petrov–Galerkin pressure-stabilizing Petrov–Galerkin formulation for incompressible Navier–Stokes equations can be used for finite element computations of high Reynolds number incompressible flow using equal order of finite element space (i.e. ) by introducing additional stabilization terms in the Navier–Stokes Galerkin formulation.