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A concurrent programming language is defined as one which uses the concept of simultaneously executing processes or threads of execution as a means of structuring a program. A parallel language is able to express programs that are executable on more than one processor.
PHP—multithreading support with parallel extension implementing message passing inspired from Go [16] Pict—essentially an executable implementation of Milner's π-calculus; Python — uses thread-based parallelism and process-based parallelism [17] Raku includes classes for threads, promises and channels by default [18]
pthreads defines a set of C programming language types, functions and constants. It is implemented with a pthread.h header and a thread library. There are around 100 threads procedures, all prefixed pthread_ and they can be categorized into five groups: Thread management – creating, joining threads etc. Mutexes; Condition variables
Stackless Python, or Stackless, is a Python programming language interpreter, so named because it avoids depending on the C call stack for its own stack. In practice, Stackless Python uses the C stack, but the stack is cleared between function calls. [ 2 ]
Many implementations of C and C++ support threading, and provide access to the native threading APIs of the operating system. A standardized interface for thread implementation is POSIX Threads (Pthreads), which is a set of C-function library calls. OS vendors are free to implement the interface as desired, but the application developer should ...
Pythran compiles a subset of Python 3 to C++ . [165] RPython can be compiled to C, and is used to build the PyPy interpreter of Python. The Python → 11l → C++ transpiler [166] compiles a subset of Python 3 to C++ . Specialized: MyHDL is a Python-based hardware description language (HDL), that converts MyHDL code to Verilog or VHDL code.
Schematic representation of how threads work under GIL. Green - thread holding GIL, red - blocked threads. A global interpreter lock (GIL) is a mechanism used in computer-language interpreters to synchronize the execution of threads so that only one native thread (per process) can execute basic operations (such as memory allocation and reference counting) at a time. [1]
OpenMP is an application programming interface (API) that supports multi-platform shared-memory multiprocessing programming in C, C++, and Fortran, [3] on many platforms, instruction-set architectures and operating systems, including Solaris, AIX, FreeBSD, HP-UX, Linux, macOS, Windows and OpenHarmony.