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Dashing is an extendable and programmable toolbox of interpretable ML models for understanding the resource utilization behavior of HPC applications during on-node scaling.
OSV-SCALIBR: A library for Software Composition Analysis
Arkouda (αρκούδα): Interactive Data Analytics at Supercomputing Scale 🐻
Generate train.jsonl and valid.jsonl files to use for fine-tuning Mistral and other LLMs.
ytopt: machine-learning-based autotuning and hyperparameter optimization framework using Bayesian Optimization
GraphGallery is a gallery for benchmarking Graph Neural Networks
Porter enables you to package your application artifact, client tools, configuration and deployment logic together as an installer that you can distribute, and install with a single command.
Implementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"
Must-read papers on graph neural networks (GNN)
A machine learning library for regression, which implements a new formulation of gradient boosting.
Castro (Compressible Astrophysics): An adaptive mesh, astrophysical compressible (radiation-, magneto-) hydrodynamics simulation code for massively parallel CPU and GPU architectures.
💿 Free software that works great, and also happens to be open-source Python.
Seamless operability between C++11 and Python
BCC - Tools for BPF-based Linux IO analysis, networking, monitoring, and more
Next generation of ADIOS developed in the Exascale Computing Program
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive lea…
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
The LLVM Project is a collection of modular and reusable compiler and toolchain technologies.