Popular GitHub Repositories for Openmp Parallelization

Fast inference engine for Transformer models

oneAPI Deep Neural Network Library (oneDNN)

A high-performance distributed training framework for Reinforcement Learning

Training and serving large-scale neural networks with auto parallelization.

A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends

Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.

This repository consists for gpu bootcamp material for HPC and AI

Pax is a Jax-based machine learning framework for training large scale models. Pax allows for advanced and fully configurable experimentation and parallelization, and has demonstrated industry leading model flop utilization rates.

Abstraction Library for Parallel Kernel Acceleration :llama:

Microsoft Finance Time Series Forecasting Framework (FinnTS) is a forecasting package that utilizes cutting-edge time series forecasting and parallelization on the cloud to produce accurate forecasts for financial data.

A language and compiler for irregular tensor programs.

The Lightning plugin ecosystem provides fast quantum state-vector and tensor network simulators written in C++ for use with PennyLane.

TePDist (TEnsor Program DISTributed) is an HLO-level automatic distributed system for DL models.

Automatic optimization and parallelization for Scientific Machine Learning (SciML)

SuperLearner guide: fitting models, ensembling, prediction, hyperparameters, parallelization, timing, feature selection, etc.

Adaptive Message Quantization and Parallelization for Distributed Full-graph GNN Training

Hypernetwork training considerations and implementation types in PyTorch. Includes classification and time-series examples alongside 1D GroupConv Parallelization.

distributed CNN inference at the edge, extend ncnn with CUDA, MPI+OPENMP support.

A benchmark suite for Graph Machine Learning

WIP. Veloce is a low-code Ray-based parallelization library that makes machine learning computation novel, efficient, and heterogeneous.