CUDA programming in Julia.

A framework for out-of-core and parallel execution

A benchmarking framework for the Julia language

Compiles Julia code to a standalone library (experimental)

A SDK/library for decentralized web and distributing computing projects

Julia support for native CUDA programming

MPI wrappers for Julia

MXNet Julia Package - flexible and efficient deep learning in Julia

Heterogeneous programming in Julia

Metal programming in Julia

Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R

Reusable array functionality for Julia's various GPU backends.

Package for writing high-level code for parallel high-performance stencil computations that can be deployed on both GPUs and CPUs

Provide insights about latency (TTFX) for Julia packages

Data structures in Julia to enable power systems analysis. Part of the Scalable Integrated Infrastructure Planning Initiative at the National Renewable Energy Lab.

The ParallelAccelerator package, part of the High Performance Scripting project at Intel Labs

GPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem

A Curious Cumulation of CUDA Cuisine

AMD GPU (ROCm) programming in Julia

OpenCL Julia bindings

The cheapest threads you can find!

The cheapest threads you can find!

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C binding generator and Julia interface to libclang

Julia wrapper for the ArrayFire library

Distributed Arrays in Julia

A discrete event process oriented simulation framework written in Julia. Formerly named SimJulia!

Explicit SIMD vector operations for Julia

Julia interface to AWS

Almost trivial distributed parallelization of stencil-based GPU and CPU applications on a regular staggered grid

Reusable compiler infrastructure for Julia GPU backends.

A Julia/JuMP Package for Unbalanced Power Network Optimization

Composable Loggers for the Julia Logging StdLib

Julia wrapper for the LLVM C API

High Performance Analytics Toolkit (HPAT) is a Julia-based framework for big data analytics on clusters.

Divide and Conquer Linear Algebra

Large-scale, distributed, sparse linear algebra in Julia.

Tools for building non-allocating pre-cached functions in Julia, allowing for GC-free usage of automatic differentiation in complex codes

Readily pin Julia threads to CPU-threads

Concurrent computing in Julia based on the Actor Model