There are 10 repositories under source-to-source topic.
An experimental Python-to-C transpiler and domain specific language for embedded high-performance computing
The implementation of the Rascal meta-programming language (including interpreter, type checker, parser generator, compiler and JVM based run-time system)
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
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
C++ compile-time programming (serialization, reflection, code modification, enum to string, better enum, enum to json, extend or parse language, etc.)
The Mython extensible variant of the Python programming language.
DEPRECATED. USE INSTEAD: https://github.com/blockspacer/flex_squarets_plugin
IIT Madras OpenMP (IMOP) compiler framework is an open-source, source-to-source, OpenMP-aware compiler for OpenMP (and serial) C programs.
GHC plugin to rewrite lens Template Haskell splices into pure functions
Yet simple but yet effective programming langauge
An optimizing Brainfuck compiler & interpreter
TC Optimizing Compiler
Custom programming language built with ANTLR4 utilising source-to-source compilation, with an ASP.NET Core RESTful API for interactivity.
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.
C++ pimpl code generator. Fast pimpl without overhead! No dynamic memory allocation! Cache-friendly! Auto-detects storage size! Generates methods based on implementation!
Interpreter for GPSS that was written on python.
Shader language and compiler
List of Transpilers, TransCompilers, Decompilers, etc, source to source converter, & similar & related tools/apps
Converts python files to starlark (or Larky) compatible scripts.