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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.
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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.
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.
Designs of parallel processors use special buses like crossbar so that the communication overhead will be small but it is the parallel algorithm that decides the volume of the traffic. If the communication overhead of additional processors outweighs the benefit of adding another processor, one encounters parallel slowdown.
In grammar, parallelism, also known as parallel structure or parallel construction, is a balance within one or more sentences of similar phrases or clauses that have the same grammatical structure. [1] The application of parallelism affects readability and may make texts easier to process. [2]
Analysis of parallel algorithms is usually carried out under the assumption that an unbounded number of processors is available. This is unrealistic, but not a problem, since any computation that can run in parallel on N processors can be executed on p < N processors by letting each processor execute multiple units of work.
For simple loops, where each iteration is independent of the others, loop-level parallelism can be embarrassingly parallel, as parallelizing only requires assigning a process to handle each iteration. However, many algorithms are designed to run sequentially, and fail when parallel processes race due to dependence within the code. Sequential ...