Program Composition Notation

Program Composition Notation (PCN) is a specification notation for building up larger programs from smaller modules or programs (usually written in C or Fortran). Efficient parallel programming is at the heart of PCN. Larger composed programs are intended to execute efficiently on single-processor machines, multiprocessors with shared memory or distributed multicomputers.

PCN was developed at Argonne National Laboratory and the California Institute of Technology.

PCN includes the language for specifying concurrent algorithms and interfaces to C and Fortran. There is also a PCN toolkit for workstations that allows applications to be developed for supercomputers which includes debugging and performance analysis tools.

PCN is appropriate for applications benefiting from parallel computing such as fluid dynamics, and climate modelling.

Sources

[1]A Primer for Program Composition Notation
[2]The Free Online Dictionary of Computing

v t e Parallel computing
General	Distributed computing Parallel computing Parallel algorithm 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) Simultaneous and heterogenous 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
Coordination	Multiprocessing Memory coherence Cache coherence 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 Array processing (SIMT) Pipelined processing Associative processing 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 Beowulf cluster Grid computer Hardware acceleration
APIs	Ateji PX Boost Chapel HPX Charm++ Cilk Coarray Fortran CUDA Dryad C++ AMP Global Arrays GPUOpen MPI OpenMP OpenCL OpenHMPP OpenACC Parallel Extensions PVM pthreads RaftLib ROCm UPC TBB ZPL
Problems	Automatic parallelization Deadlock Deterministic algorithm Embarrassingly parallel Parallel slowdown Race condition Software lockout Scalability Starvation
Category: Parallel computing