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The Message Passing Interface (MPI) is a portable message-passing standard designed to function on parallel computing architectures. [1] The MPI standard defines the syntax and semantics of library routines that are useful to a wide range of users writing portable message-passing programs in C, C++, and Fortran.
The system is designed for hierarchical based systems with homogeneous or heterogeneous CPU cores which have local memories, connected via DMA engines or similar memory transfer models. Sieve has been shown [8] successfully operating on multi-core x86 systems, the Ageia PhysX Physics Processing Unit , and the IBM Cell microprocessor .
Mainstream parallel programming languages remain either explicitly parallel or (at best) partially implicit, in which a programmer gives the compiler directives for parallelization. A few fully implicit parallel programming languages exist—SISAL, Parallel Haskell, SequenceL, System C (for FPGAs), Mitrion-C, VHDL, and Verilog.
OpenMP is an application programming interface (API) that supports multi-platform shared-memory multiprocessing programming in C, C++, and Fortran, [3] on many platforms, instruction-set architectures and operating systems, including Solaris, AIX, FreeBSD, HP-UX, Linux, macOS, and Windows.
(NB. Uses the term Occam transpiler as a synonym for a source-to-source compiler working as a pre-processor that takes a normal occam program as input and derives a new occam source code as output with link-to-channel assignments etc. added to it thereby configuring it for parallel processing to run as efficient as possible on a network of ...
In computing, a parallel programming model is an abstraction of parallel computer architecture, with which it is convenient to express algorithms and their composition in programs. The value of a programming model can be judged on its generality : how well a range of different problems can be expressed for a variety of different architectures ...
Loop-level parallelism is a form of parallelism in software programming that is concerned with extracting parallel tasks from loops.The opportunity for loop-level parallelism often arises in computing programs where data is stored in random access data structures.
This is a property of a system—whether a program, computer, or a network—where there is a separate execution point or "thread of control" for each process. A concurrent system is one where a computation can advance without waiting for all other computations to complete. [1] Concurrent computing is a form of modular programming.