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Parallel process is a phenomenon noted in clinical supervision by therapist and supervisor, whereby the therapist recreates, or parallels, the client's problems by way of relating to the supervisor. The client's transference and the therapist's countertransference thus re-appear in the mirror of the therapist/supervisor relationship.
Single instruction, multiple data. Single instruction, multiple data (SIMD) is a type of parallel processing in Flynn's taxonomy.SIMD can be internal (part of the hardware design) and it can be directly accessible through an instruction set architecture (ISA), but it should not be confused with an ISA.
"Embarrassingly" is used here to refer to parallelization problems which are "embarrassingly easy". [4] The term may imply embarrassment on the part of developers or compilers: "Because so many important problems remain unsolved mainly due to their intrinsic computational complexity, it would be embarrassing not to develop parallel implementations of polynomial homotopy continuation methods."
emmtrix Parallel Studio is a source-to-source parallelization tool combined with an interactive GUI developed by emmtrix Technologies GmbH. 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.
Bit-level parallelism is a form of parallel computing based on increasing processor word size. Increasing the word size reduces the number of instructions the processor must execute in order to perform an operation on variables whose sizes are greater than the length of the word.
Task parallelism (also known as function parallelism and control parallelism) is a form of parallelization of computer code across multiple processors in parallel computing environments. Task parallelism focuses on distributing tasks —concurrently performed by processes or threads —across different processors.
Parallel computing is a type of computation in which many calculations or processes are carried out simultaneously. [1] Large problems can often be divided into smaller ones, which can then be solved at the same time. There are several different forms of parallel computing: bit-level, instruction-level, data, and task parallelism.
Concurrent computations may be executed in parallel, [3] [6] for example, by assigning each process to a separate processor or processor core, or distributing a computation across a network. The exact timing of when tasks in a concurrent system are executed depends on the scheduling , and tasks need not always be executed concurrently.