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(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 ...
Concurrent and parallel programming languages involve multiple timelines. Such languages provide synchronization constructs whose behavior is defined by a parallel execution model . A concurrent programming language is defined as one which uses the concept of simultaneously executing processes or threads of execution as a means of structuring a ...
A skilled parallel programmer may take advantage of explicit parallelism to produce efficient code for a given target computation environment. However, programming with explicit parallelism is often difficult, especially for non-computing specialists, because of the extra work and skill involved in developing it.
It takes C, MATLAB, Simulink, Scilab or Xcos source code as input and generates parallel C code as output. It relies on static schedule and a message passing API for the parallel program. The whole parallelization process is controlled and visualized in an interactive GUI enabling parallelization decisions by the end user.
It is a C++ template library with six data-parallel and one task-parallel skeletons, two container types, and support for execution on multi-GPU systems both with CUDA and OpenCL. Recently, support for hybrid execution, performance-aware dynamic scheduling and load balancing is developed in SkePU by implementing a backend for the StarPU runtime ...
As a simple example, if a system is running code on a 2-processor system (CPUs "a" & "b") in a parallel environment and we wish to do tasks "A" and "B", it is possible to tell CPU "a" to do task "A" and CPU "b" to do task "B" simultaneously, thereby reducing the run time of the execution.
If statement S1 takes T time to execute, then the loop takes time n * T to execute sequentially, ignoring time taken by loop constructs. Now, consider a system with p processors where p > n. If n threads run in parallel, the time to execute all n steps is reduced to T. Less simple cases produce inconsistent, i.e. non-serializable outcomes.
Automatic vectorization, in parallel computing, is a special case of automatic parallelization, where a computer program is converted from a scalar implementation, which processes a single pair of operands at a time, to a vector implementation, which processes one operation on multiple pairs of operands at once.