CUDA.jl 3.0 was a major release of the NVIDIA GPU programming support package for Julia, with a major addition to the programming model: support for concurrent GPU programming with Julia tasks. In this talk, I will explain what concurrent GPU programming means, how it works, and how you can use it to improve your GPU programs.

I will also talk about other features and changes that are part of CUDA.jl 3.0 and more recent releases, such as the new device-side random number generator, support for building computational graphs, the new memory allocator, etc.