Concurrency

• Julia HPC and Cluster computing.
• Distributed Computing and Grid computing.
• Cloud computing
• Parallel computing
• Hardware architectures (ARM, CUDA, GPU, MIPS) anb compute kernels

Organizations

• Julia Parallel
• Julia Folds
• Julia Cloud

Resources

• Julia manual for parallel computing
• Wikipedia: Concurrency
• Wikipedia: Parallel Computing

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General Concurrency Packages

• JuliaActors/Actors.jl : Actor Model concurrent model.
• JuliaArrays/TiledIteration.jl : Julia package to facilitate writing mulithreaded, multidimensional, cache-efficient code.
• JuliaFolds/Folds.jl : A unified interface for sequential, threaded, and distributed folds. The docs list what functions it supports.
• JuliaParallel/MessageUtils.jl : A collection of utilities for messaging.

Bindings

• JuliaGPU/ArrayFire.jl : Julia Wrapper for the ArrayFire library.
• JuliaLinearAlgebra/AppleAccelerate.jl : Julia interface to OS X's Accelerate framework.
• JuliaParallel/Elly.jl : Hadoop HDFS and Yarn client.
• JuliaParallel/Hwloc.jl : Wrapper to the hwloc library to provide a portable abstraction (across OS, versions, architectures, ...) of the hierarchical topology of modern architectures, including NUMA memory nodes, sockets, shared caches, cores and simultaneous multithreading.

Cloud computing

• JuliaCloud/AWS.jl : supports the EC2 and S3 API's, letting you start and stop EC2 instances dynamically.
• JuliaCloud/AWSCore.jl : Amazon Web Services Core Functions and Types.
• JuliaCloud/AWSS3.jl : AWS S3 Simple Storage Service interface for Julia.
• JuliaCloud/GoogleCloud.jl : Google Cloud APIs for Julia.
• JuliaComputing/Kuber.jl : Julia Kubernetes Client.

SIMD Computing

• Wikipedia: SIMD Computing.
• Julia docs: @simd macro.

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• eschnett/SIMD.jl : Explicit SIMD vector operations for Julia.
• JuliaSIMD/LoopVectorization.jl : vectorize your for loop using the @turbo macro.

Multi-Threading

• carstenbauer/ThreadPinning.jl : Pin Julia threads to CPU processors. Requires the lscpu` command (in virtually all Linux systems). JuliaCon 2023
• JuliaFolds/FLoops.jl : the macro @floop, a superset of Threads.@threads, for a fast generic iteration over complex collections.
• tkf/ThreadsX.jl : Multithreaded base functions such as map(), reduce(), foreach().

Multiprocessing and Distributed Computing

• Wikipedia: Distributed Computing across multiple compute nodes.
• Wikipedia: Job Scheduler
• Julia at scale topic on discourse.
• magerton/FARMTest.jl : Simple example scripts for running Julia on a SLURM cluster, using kleinhenz/SlurmClusterManager.jl

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• ChevronETC/Schedulers.jl : It provides elastic and fault tolerant parallel map and parallel map reduce methods.
• ChrisRackauckas/ParallelDataTransfer.jl : A bunch of helper functions for transferring data between worker processes.
• eschnett/Persist.jl : Running jobs in the background, independent of the Julia shell.
• JuliaParallel/ClusterManagers.jl : Support for different clustering technologies.
• JuliaParallel/Dagger.jl : A framework for out-of-core and parallel computation and hierarchical Scheduling of DAG Structured Computations. Similar to dask library in Python.
• JuliaParallel/DistributedArrays.jl : A task persistency mechanism based on hash-graphs for Dispatcher.jl.
• JuliaParallel/MPI.jl : Julia interface to the Message Passing Interface (MPI)
• JuliaPluto/Malt.jl : a multiprocessing package for Julia. It is used by fonsp/Pluto.jl to manage the Julia process that notebook code is executed in, as a replacement to Distributed.
• kleinhenz/SlurmClusterManager.jl : julia package for running code on slurm clusters. See magerton/FARMTest.jl for simple example scripts.
• zgornel/DispatcherCache.jl : Tool for building and executing a computation graph given a series of dependent operations.

GPU computing

• Wikipedia: GPGPU
• Sample OpenCL notebooks for GPU Julia, and GPU Transpose.
• Blog post on High-Performance GPU Computing in the Julia Programming Language.

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• hjabird/CVortex.jl : Julia wrapper for cvortex GPU accelerated vortex filament and vortex particle methods.
• JuliaGPU/AMDGPU.jl : AMD GPU (ROCm) programming in Julia.
• JuliaGPU/ArrayFire.jl : Julia Wrapper for the ArrayFire library.

NVIDIA CUDA

• JuliaFolds/FoldsCUDA.jl : provides Transducers.jl-compatible fold (reduce) implemented using CUDA.jl. This brings the transducers and reducing function combinators implemented in Transducers.jl to GPU. Furthermore, using FLoops.jl, you can write parallel for loops that run on GPU.
• JuliaGPU/CUDA.jl : CUDA programming in Julia. See also JuliaCon 2021 video.
• JuliaGPU/NVTX.jl : Julia bindings for NVTX, for instrumenting with the Nvidia Nsight Systems profiler. JuliaCon 2023 video.
• xiaodaigh/CuCountMap.jl : Fast StatsBase.countmap for small types on the GPU via CUDA.jl