

Flagcx
Overview :
FlagCX is a scalable and adaptive cross-chip communication library supported by the Beijing Academy of Artificial Intelligence (BAAI). It is part of the FlagAI-Open open-source initiative aimed at fostering an open-source ecosystem for AI technologies. FlagCX utilizes native collective communication libraries and comprehensively supports single-chip communication across different platforms. Supported communication backends include NCCL, IXCCL, and CNCL.
Target Users :
FlagCX is aimed at AI developers, researchers, and enthusiasts who require efficient data communication across various hardware platforms. Due to its open-source nature and support for multiple communication backends, this product is suitable for users engaged in large-scale data processing and high-performance computing.
Use Cases
Data parallel processing in AI model training.
Efficient communication between multiple chips in deep learning frameworks.
Used as an open-source project by developers and researchers worldwide for various AI-related research and development work.
Features
Supports single-chip communication across different platforms.
Provides comprehensive support for cross-chip communication.
Utilizes native collective communication libraries such as NCCL, IXCCL, and CNCL.
Offers build and test guidelines for easy use and testing by developers.
Supports custom build paths and installation paths for runtime and communication libraries.
Provides a variety of test parameters to accommodate different performance testing needs.
How to Use
1. Clone the repository: Use the git clone command to clone the FlagCX codebase.
2. Build the library: Navigate to the FlagCX directory and use the make command with the appropriate platform flag to build.
3. Test performance: In the test/perf directory, use the make command to build the test programs and run the test, for example, by using ./test_allreduce -b 128M -e 8G -f 2 to perform a performance test.
4. Adjust test parameters: Modify test parameters as needed, such as using -b, -e, and -f options to set the size range and increments of the test data.
5. Review documentation: Visit the FlagCX GitHub page to review the README and LICENSE files for more usage and licensing information.
6. Contribute code: Developers are encouraged to contribute to FlagCX, helping to advance the project.
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