Degree of parallelism

The degree of parallelism (DOP) is a metric which indicates how many operations can be or are being simultaneously executed by a computer. It is especially useful for describing the performance of parallel programs and multi-processor systems.

A program running on a parallel computer may utilize different numbers of processors at different times. For each time period, the number of processors used to execute a program is defined as the degree of parallelism. The plot of the DOP as a function of time for a given program is called the parallelism profile.

Parallel computing
General	Distributed computing Parallel computing Massively parallel Cloud computing High-performance computing Multiprocessing Manycore processor GPGPU Computer network Systolic array
Levels	Bit Instruction Thread Task Data Memory Loop Pipeline
Multithreading	Temporal Simultaneous (SMT) Speculative (SpMT) Preemptive Cooperative Clustered Multi-Thread (CMT) Hardware scout
Theory	PRAM model PEM Model Analysis of parallel algorithms Amdahl's law Gustafson's law Cost efficiency Karp–Flatt metric Slowdown Speedup
Elements	Process Thread Fiber Instruction window Array data structure
Coordination	Multiprocessing Memory coherency Cache coherency Cache invalidation Barrier Synchronization Application checkpointing
Programming	Stream processing Dataflow programming Models Implicit parallelism Explicit parallelism Concurrency Non-blocking algorithm
Hardware	Flynn's taxonomy SISD SIMD SIMT MISD MIMD Dataflow architecture Pipelined processor Superscalar processor Vector processor Multiprocessor symmetric asymmetric Memory shared distributed distributed shared UMA NUMA COMA Massively parallel computer Computer cluster Grid computer Hardware acceleration
APIs	Ateji PX Boost.Thread Chapel HPX Charm++ Cilk Coarray Fortran CUDA HIP Dryad C++ AMP Global Arrays MPI OpenMP OpenCL OpenHMPP OpenACC TPL PLINQ PVM POSIX Threads RaftLib UPC TBB ZPL
Problems	Automatic parallelization Deadlock Livelock Deterministic algorithm Embarrassingly parallel Parallel slowdown Race condition Software lockout Scalability Starvation
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