# Get Ready for Clojure, GPU, and AI in 2026 with CUDA 13.0

DevFeed: [Get Ready for Clojure, GPU, and AI in 2026 with CUDA 13.0](<https://devfeed.tech/articles/get-ready-for-clojure-gpu-and-ai-in-2026-with-cuda-13-0-20730.md>)

Original publisher: [Read original article](<http://dragan.rocks/articles/25/Get-Ready-Clojure-GPU-AI-2026-CUDA-13>)

Published: 2025-10-30T16:37:00Z

Content type: tutorial

Language: en

Sources: [Dragan Djuric](<https://devfeed.tech/sources/dragan-djuric.md>)

Topics: [Clojure](<https://devfeed.tech/topics/clojure.md>), [CUDA](<https://devfeed.tech/topics/cuda.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [OpenCL](<https://devfeed.tech/topics/opencl.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [c-plus-plus](<https://devfeed.tech/tags/c-plus-plus.md>), [clojure](<https://devfeed.tech/tags/clojure.md>), [coding](<https://devfeed.tech/tags/coding.md>), [cuda](<https://devfeed.tech/tags/cuda.md>), [deep](<https://devfeed.tech/tags/deep.md>), [diamond](<https://devfeed.tech/tags/diamond.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [opencl](<https://devfeed.tech/tags/opencl.md>), [tensors](<https://devfeed.tech/tags/tensors.md>)

## AI overview

The article introduces ClojureCUDA 0.25.0, which supports CUDA 13.0.2, and encourages Clojure developers to try GPU programming interactively through the Clojure REPL. It explains that GPU acceleration is most useful for large vectors and sufficiently complex workloads because data transfer costs can outweigh computation gains.

## Source excerpt

A little anniversary Did you know that CUDA has been available in Clojure for the last 9 years through ClojureCUDA, and GPU programming through OpenCL for more than 10? I almost forgot about these anniversaries. Ten years ago most people liked it a lot, starred it on Github, patted me on the back, but then concluded that they don't have an Nvidia card available on their laptops, or, if they had GPUs, that they won't have time to learn to think in massive parallel algorithms, or if they have time and will, that there are no GPUs in the servers, so what would they do with their applications, even if they created them in Clojure, and so on, and so off :) But, ClojureCUDA and ClojureCL continued living on for these 10 years, I used them in creating Neanderthal, Deep Diamond, and Diamond ML, and they proved themselves as simple and reliable tools. I still had trouble convincing Clojure programmers that they can write GPU programs that run as fast as they'd wrote them in C++, but interactively in the Cloujre REPL, without C++ hell. But I'm not easy to shake off! If it's necessary, I'll continue for 10 more years, for I'm convinced there'd be a moment when Clojure programmers are going to say "hmmm, this is something that we can use and be good at!". CUDA 13 is here! I've recently released ClojureCUDA 0.25.0, with support for the latest CUDA 13.0.2! Why not celebrate that by opening the REPL, and coding your first Hello World application on the GPU? I promise, it won't be a usual GPU carpet of text; this is ClojureCUDA, it follows the Clojure philosophy by being simple and interactive! There's not much sense in wielding a GPU to print out "Hello World". Note that it is also not very useful to work with scalar numbers and call a GPU function to add or multiply two numbers. No. Unless you have many, many, numbers to crunch, stay by your trusty CPU. For our purposes, many, many, numbers would be two vectors of dimension 3 (hey, it's hello world; imagine it's 3 billion). Also,