♠️ C# to JavaScript compiler. Write modern mobile and web apps in C#. Run anywhere with Bridge.NET.

A universal translator for programming languages

The implementation of the Rascal meta-programming language (including interpreter, type checker, parser generator, compiler and JVM based run-time system)

Coding time Compile. A tool to write code fastest.

Access 3600+ libraries from C# and let Bridge.NET compile your project into JavaScript.

A Swift Package Manager console app and library to convert Objective-C code into Swift.

Tool for translation type comments to type annotations in Python

Tools for rapid prototyping of DSL compilers

DEPRECATED. USE INSTEAD github.com/blockspacer/flextool

Mercurium is a C/C++/Fortran source-to-source compilation infrastructure aimed at fast prototyping developed by the Programming Models group at the Barcelona Supercomputing Center

CLAW Compiler for Performance Portability

FLPR: The Fortran Language Program Remodeling system

The Mython extensible variant of the Python programming language.

DEPRECATED. USE INSTEAD: https://github.com/blockspacer/flex_squarets_plugin

An experimental Python-to-C transpiler and domain specific language for embedded high-performance computing

Convert Flow declarations to TypeScript

C++ compile-time programming (serialization, reflection, code modification, enum to string, better enum, enum to json, extend or parse language, etc.)

PL/SQL to Python transcompiler

TC Optimizing Compiler

GHC plugin to rewrite lens Template Haskell splices into pure functions

Shader language and compiler

An optimizing Brainfuck compiler & interpreter

Custom programming language built with ANTLR4 utilising source-to-source compilation, with an ASP.NET Core RESTful API for interactivity.

APReF: An Automatic Parallelizer of Recursive Functions for Haskell

Source to source compiler for Extended C Language(CX)

Yet simple but yet effective programming langauge

Recent development in Graphic Processing Units (GPUs) has opened a new challenge in harnessing their computing power as a new general-purpose computing paradigm with its CUDA parallel programming. However, porting applications to CUDA remains a challenge to average programmers. We have developed a restructuring software compiler (RT-CUDA) with best possible kernel optimizations to bridge the gap between high-level languages and the machine dependent CUDA environment. RT-CUDA is based upon a set of compiler optimizations. RT-CUDA takes a C-like program and convert it into an optimized CUDA kernel with user directives in a con.figuration .file for guiding the compiler. While the invocation of external libraries is not possible with OpenACC commercial compiler, RT-CUDA allows transparent invocation of the most optimized external math libraries like cuSparse and cuBLAS. For this, RT-CUDA uses interfacing APIs, error handling interpretation, and user transparent programming. This enables efficient design of linear algebra solvers (LAS). Evaluation of RT-CUDA has been performed on Tesla K20c GPU with a variety of basic linear algebra operators (M+, MM, MV, VV, etc.) as well as the programming of solvers of systems of linear equations like Jacobi and Conjugate Gradient. We obtained significant speedup over other compilers like OpenACC and GPGPU compilers. RT-CUDA facilitates the design of efficient parallel software for developing parallel simulators (reservoir simulators, molecular dynamics, etc.) which are critical for Oil & Gas industry. We expect RT-CUDA to be needed by many industries dealing with science and engineering simulation on massively parallel computers like NVIDIA GPUs.

A Python to C Compiler in Rust