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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A streamlined CMake build system foundation for developing HPC software
| Date | Stars |
|---|---|
| 2026-07-24 | 294 |
| 2026-07-25 | 294 |
| 2026-07-28 | 294 |
| 2026-07-30 | 294 |
| 2026-08-19 | 295 |
| 2026-08-20 | 296 |
| 2026-08-21 | 296 |
| 2026-09-11 | 296 |
| 2026-09-15 | 296 |
| 2026-09-19 | 296 |
| 2026-09-20 | 296 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
5.0
growth rate 0.00%/day
# <img src="/share/blt/logo/blt_logo_transparent.png?raw=true" width="128" valign="middle" alt="BLT"/>
[](https://dev.azure.com/llnl-blt/blt/_build/latest?definitionId=1&branchName=develop)
[](https://llnl-blt.readthedocs.io/en/develop/?badge=develop)
BLT is a streamlined [CMake](https://cmake.org)-based foundation for
<b>B</b>uilding, <b>L</b>inking and <b>T</b>esting large-scale high performance computing (HPC) applications.
BLT makes it easy to get up and running on a wide range of HPC compilers,
operating systems and technologies:
* Compiler families:
[gcc](https://gcc.gnu.org),
[clang](https://clang.llvm.org),
[Intel](https://software.intel.com/en-us/compilers),
[XL](https://www.ibm.com/us-en/marketplace/ibm-c-and-c-plus-plus-compiler-family),
[Visual Studio](https://visualstudio.microsoft.com/vs/features/cplusplus)
* Operating systems:
Linux,
Mac OS,
Windows
* HPC programming models:
[MPI](https://www.mpi-forum.org/),
[OpenMP](https://www.openmp.org/),
[CUDA](https://developer.nvidia.com/cuda-zone),
[HIP](https://gpuopen.com/compute-product/hip-convert-cuda-to-portable-c-code)
* Unit testing and benchmarking (built-in):
[Google Test (gtest and gmock)](https://github.com/google/googletest),
[FRUIT](https://sourceforge.net/projects/fortranxunit),
[gbenchmark](https://github.com/google/benchmark)
* Documentation:
[Doxygen](http://www.doxygen.nl/),
[Sphinx](http://www.sphinx-doc.org)
* Code style:
[AStyle](http://astyle.sourceforge.net),
[ClangFormat](https://clang.llvm.org/docs/ClangFormat.html),
[cmake-format](https://github.com/cheshirekow/cmake_format),
[Uncrustify](http://uncrustify.sourceforge.net),
[YAPF (Yet Another Python Formatter)](https://github.com/google/yapf)
* Code quality
[clang-query](http://clang.llvm.org/docs/LibASTMatchers.html),
[clang-tidy](https://clang.llvm.org/extra/clang-tidy),
[Cppcheck](http://cppcheck.sourceforge.net)
Getting started
---------------
BLT is easy to pull into an existing or new CMake-based project using a single CMake `include()` command:
```cmake
include(path/to/blt/SetupBLT.cmake)
```
For more information, please check our [user documentation and tutorial](https://llnl-blt.readthedocs.io).
Questions
---------
Any questions can be sent to [email protected]. If you are an LLNL employee or collaborator, we have an
internal Microsoft Teams group chat named "BLT" as well.
Contributions
-------------
We welcome all kinds of contributions: new features, bug fixes, documentation edits.
To contribute, make a [pull request](https://github.com/LLNL/blt/pulls), with `develop`
as the destination branch. We use CI testing and your branch must pass these tests before
being merged.
For more information, see the [contributing guide](https://github.com/LLNL/blt/blob/develop/CONTRIBUTING.md).
Authors
-------
Thanks to all of BLT's [contributors](https://github.com/LLNL/blt/graphs/contributors).
Open-Source Projects using BLT
------------------------------
* [Adiak](https://github.com/LLNL/Adiak): Library for collecting metadata from HPC application runs
* [Ascent](https://github.com/Alpine-DAV/ascent): A flyweight in-situ visualization and analysis runtime for multi-physics HPC simulations
* [Axom](https://github.com/LLNL/axom): Software infrastructure for the development of multi-physics applications and computational tools
* [CARE](https://github.com/LLNL/CARE): CHAI and RAJA extensions
* [CHAI](https://github.com/LLNL/CHAI): Copy-hiding array abstraction to automatically migrate data between memory spaces
* [Conduit](https://github.com/LLNL/conduit): Simplified data exchange for HPC simulations
* [Comb](https://github.com/LLNLExcerpt of 6,951 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:358974ef9e74cd69, topic:cuda, topic:hpc
matched fp:358974ef9e74cd69, topic:testing