Aluminum

Aluminum is a high-performance communication library for CPUs, GPUs, and other accelerator platforms. It leverages existing libraries, such as MPI, NCCL, and RCCL, plus its own infrastructure, to deliver performance and accelerator-centric communication.

Aluminum is open-source and maintained by the Lawrence Livermore National Laboratory. If you use Aluminum, please cite our paper:

@inproceedings{dryden2018aluminum,
  title={Aluminum: An Asynchronous, {GPU}-Aware Communication Library Optimized for Large-Scale Training of Deep Neural Networks on {HPC} Systems},
  author={Dryden, Nikoli and Maruyama, Naoya and Moon, Tim and Benson, Tom and Yoo, Andy and Snir, Marc and Van Essen, Brian},
  booktitle={Proceedings of the Workshop on Machine Learning in HPC Environments (MLHPC)},
  year={2018}
}

Features

Support for blocking and non-blocking collective and point-to-point operations
Accelerator-centric communication
Supported communication backends:
- MPI: Uses the Message Passing Interface and supports any hardware your underlying MPI library supports.
- NCCL: Uses either Nvidia's NCCL library for Nvidia GPUs or AMD's RCCL library for AMD GPUs.
- HostTransfer: Uses MPI plus the CUDA or HIP runtime to support Nvidia or AMD GPUs without specialized libraries.

Getting Started

For full details, see the Aluminum documentation.

For basic usage examples, see the examples.

Building and Installation

Aluminum is available via Spack or can be installed manually from source.

Source builds need a recent CMake, C++ compiler (with support for C++17), MPI, and hwloc. Accelerator backends need the appropriate runtime libraries.

A basic out-of-source build can be done with

mkdir build && cd build
cmake /path/to/Aluminum/source

For full details on building, configuration, testing, and benchmarking, see the documentation.

Authors

License