All Algorithms implemented in Python

Solve puzzles. Learn CUDA.

Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.

Blog posts on best practices for Julia development

Manage your Julia dependencies from Python

Python and Julia in harmony.

Quantum Toolbox in Julia

A lightweight library for portable low-level GPU computation using WebGPU.

Inline graphics in the REPL using Sixel

Beautiful and flexible vizualizations of high dimensional data

Jupyter notebook scripts for the course Programming Large-Scale Parallel Systems (XM_40017) at Vrije Universiteit Amsterdam.

LLM training in simple, raw C/CUDA

A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API

A simple & elegant experiment tracking framework that integrates persistence logic & best practices directly into Python

A collection of design patterns/idioms in Python

CUDA programming in Julia.

The dispatch doctor prescribes type stability

Tile primitives for speedy kernels

Routines for batching regular code and make them fast!

Heterogeneous programming in Julia

An interface to various automatic differentiation backends in Julia.

Implementation of the 12 steps approach to the Navier-Stokes equations, essential for simulating fluid dynamics.

Functionality for working efficiently with block diagonal matrices.

Bring Your Own Stack

LinearSolve.jl: High-Performance Unified Interface for Linear Solvers in Julia. Easily switch between factorization and Krylov methods, add preconditioners, and all in one interface.

A Julia package to represent strided views over a parent DenseArray

Sparse tensors in Julia and more! Datastructure-driven array programing language.

High-Resolution Image Synthesis with Latent Diffusion Models