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Interactive GPU Programming, Part 1: Hello CUDA
Today, fast number crunching means parallel programs that run on Graphical Processing Units (GPUs). Thanks to the recent highly publicized deep learning and ...
Dragan Djuric
Dragan Djuric's Clojure Blog, Artificial Intelligence, Deep Learning, Bayesian Data Analysis, CUDA, GPU, OpenCL, Functional Programming, Probabilistic Programming, Data Science.
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Visit dragan.rocks → RSS feedOn Hacker News Jun 2017 – Apr 2020
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CUDA 10 in Clojure
CUDA 10 support has just landed in ClojureCUDA with the latest version 0.6.0.
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Interactive GPU Programming, Part 2: Hello OpenCL
This is really the same article as Part 1 - Hello CUDA, but with the focus on OpenCL, so I'll skip most of the narration and just show you the code.
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Foundations of ML and AI: Book recommendations
Here's what I recommend to programmers if they want to understand machine learning. Six fantastic books that you can work with in your spare time to build yo...
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Fast Tensors in Clojure – A Sneak Peek
There's a lot going on behind the scenes, since I am not only writing the books; at the same time I have to create the software to write about. For example, ...
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CuPy Accelerates NumPy on the GPU? Hold My Cider, Here's Clojure
Everyone knows that Java is slow and Clojure is not a great choice for number crunching, but as soon as I dig anywhere with my software, I discover that the ...
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Deep Learning in Clojure from Scratch to GPU: Learning a Regression
A great moment has arrived. We are going to apply our neural networks implementation to a regression problem. The network is going to learn a known function,...
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Clojure from Scratch to GPU: A Simple Neural Network Training API
The stage has been set for wrapping up the simplest version of a complete neural network API, and its key part that offers the entry for the /learning/ funct...
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Deep Learning from Scratch to GPU: CUDA and OpenCL
We generalize the network code and run it on the GPU. On an Nvidia GPU with CUDA, and on an AMD GPU with OpenCL. Even more - we mix both CUDA and OpenCL, jus...
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Deep Learning on the GPU in Clojure from Scratch: Sharing Memory
Sharing and reusing memory buffers is inescapable if we want high performance. It is a sharp but powerful tool.
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Neanderthal vs. ND4J – Native Performance, Java and CPU
Today, Java has a choice of a few well maintained libraries that can use Intel's MKL for fast native operations. MKL is basically as fast as you can get toda...