Blog

Metal.jl 1.4: Improved random numbers
Oct 7, 2024

CUDA.jl 5.5: Maintenance release
Sep 18, 2024

CUDA.jl 5.4: Memory management mayhem
May 28, 2024

oneAPI.jl 1.5: Ponte Vecchio support and oneMKL improvements
May 24, 2024

CUDA.jl 5.2 and 5.3: Maintenance releases
Apr 26, 2024

CUDA.jl 5.1: Unified memory and cooperative groups
Nov 7, 2023

CUDA.jl 5.0: Integrated profiler and task synchronization changes
Sep 19, 2023

Profiling oneAPI.jl applications with VTune
Jul 19, 2023

Metal.jl 0.2: Metal Performance Shaders
Mar 3, 2023

oneAPI.jl 1.0: oneMKL, Intel Arc and Julia 1.9
Feb 8, 2023

CUDA.jl 4.0
Feb 1, 2023

Technical preview: Programming Apple M1 GPUs in Julia with Metal.jl
Jun 24, 2022

oneAPI.jl status update
Apr 6, 2022

CUDA.jl 3.5-3.8
Jan 28, 2022

CUDA.jl 3.4
Aug 13, 2021

CUDA.jl 3.3
Jun 10, 2021

CUDA.jl 3.0
Apr 9, 2021

CUDA.jl 2.4 and 2.5
Jan 8, 2021

Introducing: oneAPI.jl
Nov 5, 2020

CUDA.jl 2.1
Oct 30, 2020

CUDA.jl 2.0
Oct 2, 2020

Paper: Flexible Performant GEMM Kernels on GPUs
Sep 28, 2020

CUDA.jl 1.3 - Multi-device programming
Jul 18, 2020

CUDA.jl 1.1
Jul 7, 2020

CUDAnative.jl 3.0 and CuArrays.jl 2.0
Mar 25, 2020

Julia's Dramatic Rise in HPC and Elsewhere  ↗
Jan 14, 2020

Accelerating Tensor Computations in Julia with the GPU  ↗
Jan 5, 2020

New website for JuliaGPU
Dec 12, 2019

Julia Computing Brings Support for NVIDIA GPU Computing on Arm Powered Servers  ↗
Dec 3, 2019

DifferentialEquations.jl v6.9.0 released with automatic Multi-GPU support  ↗
Dec 3, 2019

An Introduction to GPU Programming in Julia  ↗
Oct 17, 2019

Next Generation Climate Models leverage Julia and GPUs  ↗
Mar 4, 2019

New Climate Model to be Built from the Ground Up  ↗
Dec 12, 2018

Solving Systems of Stochastic PDEs and using GPUs in Julia  ↗
Dec 11, 2017

High-Performance GPU Computing in the Julia Programming Language  ↗
Oct 25, 2017