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Cython also facilitates wrapping independent C or C++ code into python-importable modules. Cython is written in Python and C and works on Windows, macOS, and Linux, producing C source files compatible with CPython 2.6, 2.7, and 3.3 and later versions. The Cython source code that Cython compiles (to C) can use both Python 2 and Python 3 syntax ...
Some parallel programming systems, such as OpenMP and Cilk, have language support for the map pattern in the form of a parallel for loop; [2] languages such as OpenCL and CUDA support elemental functions (as "kernels") at the language level. The map pattern is typically combined with other parallel design patterns.
Therefore, compilers will attempt to transform the first form into the second; this type of optimization is known as map fusion and is the functional analog of loop fusion. [ 2 ] Map functions can be and often are defined in terms of a fold such as foldr , which means one can do a map-fold fusion : foldr f z . map g is equivalent to foldr (f .
Automatic parallelization by compilers or tools is very difficult due to the following reasons: [6] dependence analysis is hard for code that uses indirect addressing, pointers, recursion, or indirect function calls because it is difficult to detect such dependencies at compile time; loops have an unknown number of iterations;
Nuitka (pronounced as / n juː t k ʌ / [2]) is a source-to-source compiler which compiles Python code to C source code, applying some compile-time optimizations in the process such as constant folding and propagation, built-in call prediction, type inference, and conditional statement execution.
Intel C++ Compiler, GNU Compiler Collection since GCC 6, and Clang since clang 7 allow for a simplified approach, with the compiler taking care of function duplication and selection. GCC and clang requires explicit target_clones labels in the code to "clone" functions, [20] while ICC does so automatically (under the command-line option /Qax).
Written in C and Python, CPython is the default and most widely used implementation of the Python language. CPython can be defined as both an interpreter and a compiler as it compiles Python code into bytecode before interpreting it.
To optimize this, a C++ compiler would need to: Inline the sin and operator+ function calls. Fuse the loops into a single loop. Remove the unused stores into the temporary arrays (can use a register or stack variable instead). Remove the unused allocation and free. All of these steps are individually possible.