Argonne Leadership Computing Facility - ALCF's Projects
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Example scripts and profiling demonstrations for deep learning models
Scaling Deep learning on HPC systems
An I/O benchmark for deep Learning applications
Simple tests to verify ML/DL environments on ALCF HPC resources are working correctly.
A repository for image recipe files useful for ALCF systems.
Allows passing and getting back Ruby VALUE directly to and from native code
Collection of small examples for running on ALCF resources
GPyTorch and other Gaussian Process tutorials on HPC resources
Provide examples on how to use GPU with Parallel Programing Paradigm (MPI, OpenMP, SYCL)
An introduction and guide to GitLab continuous integration at the ALCF
Walkthrough for running C++ MPI-based jobs using Jupyter Notebooks
CEED Library: Code for Efficient Extensible Discretizations
Accelerated finite element flow solvers
Repo for work on LLM Evaluation across AI accelerators
Ongoing research training transformer language models at scale, including: BERT & GPT-2
Ongoing research training transformer models at scale
SYCL code generation plugin for MadGraph5_aMC@NLO
Profiling tools for performance studies of competing ML frameworks on HPC systems
Data analytics for molecular solids melting points
Zero-copy MPI communication of JAX arrays, for turbo-charged HPC applications in Python :zap:
our next generation code
This fork contains efforts to combine Ai/ML with NekRS let by Argonne National Lab and other collaborators
JIT Compilation for Multiple Architectures: C++, OpenMP, CUDA, HIP, OpenCL, Metal
An HPC workload manager and job scheduler for desktops, clusters, and clouds.
scripts for working with PBS
Temporary documentation for Polaris resource