Explicit parallelism

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In computer programming, explicit parallelism is the representation of concurrent computations by means of primitives in the form of special-purpose directives or function calls. Most parallel primitives are related to process synchronization, communication or task partitioning. As they seldom contribute to actually carry out the intended computation of the program, their computational cost is often considered as parallelization overhead.

The advantage of explicit parallel programming is the absolute programmer control over the parallel execution. A skilled parallel programmer takes advantage of explicit parallelism to produce very efficient code. However, programming with explicit parallelism is often difficult, especially for non computing specialists, because of the extra work involved in planning the task division and synchronization of concurrent processes.

In some instances, explicit parallelism may be avoided with the use of an optimizing compiler that automatically extracts the parallelism inherent to computations (see implicit parallelism).

Programming with explicit parallelism

v t e Parallel computing

General	Cloud computing High-performance computing Cluster computing Distributed computing Grid computing

Levels	Bit Instruction Data Task

Multithreading	Temporal multithreading Simultaneous multithreading Hyper-threading

Theory	Amdahl's law Gustafson's law Cost efficiency Karp–Flatt metric slowdown speedup

Elements	Process Thread Fiber PRAM Instruction window

Coordination	Multiprocessing Memory coherency Cache coherency Cache invalidation Barrier Synchronization Application checkpointing

Programming	Models Implicit parallelism Explicit parallelism Concurrency Flynn's taxonomy SISD SIMD MISD MIMD SPMD Thread Non-blocking algorithm

Hardware	Multiprocessor Symmetric Asymmetric Memory NUMA COMA distributed shared distributed shared MPP Superscalar Vector processor Supercomputer Beowulf cluster

APIs	Ateji PX POSIX Threads OpenMP OpenHMPP OpenACC PVM MPI UPC TBB Boost.Thread Global Arrays Charm++ Cilk/Cilk Plus Coarray Fortran OpenCL CUDA Dryad C++ AMP PLINQ TPL

Problems	Embarrassingly parallel Software lockout Scalability Race condition Deadlock Livelock Starvation Deterministic algorithm Parallel slowdown

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