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AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.

Python library for converting Python calculations into rendered latex.

GPU accelerated decision optimization

A Python-embedded modeling language for convex optimization problems.

Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

Source code for the book Real-Time C++, by Christopher Kormanyos

Neural network quantization for research and prototyping

Portable GPU Programming

A curated list of materials on AI efficiency

Neural Networks with low bit weights on low end 32 bit microcontrollers such as the CH32V003 RISC-V Microcontroller and others

Welcome to the official repository of SINQ! A novel, fast and high-quality quantization method designed to make any Large Language Model smaller while preserving accuracy.

Fast low-bit matmul kernels in Triton

Measure and optimize the energy consumption of your AI applications!

Efficient AI-Enhanced 5G PUSCH Receiver

Sionna: An Open-Source Library for Research on Communication Systems

Sionna Research Kit: A GPU-Accelerated Research Platform for AI-RAN

Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.

Python code for "Probabilistic Machine learning" book by Kevin Murphy

Simulation code and accompanying material for the textbook "Introduction to Multiple Antenna Communications and Reconfigurable Surfaces" by Emil Björnson and Özlem Tuğfe Demir, Boston-Delft: now pu…

An official implementation of "Scheduling Weight Transitions for Quantization-Aware Training" (ICCV 2025) in PyTorch.

Efficient Knowledge Injection in LLMs via Self-Distillation (TMLR)

Efficient AI-Enhanced 5G PUSCH Receiver

CSC Summer School in High-Performance Computing

Code for the book "The Elements of Differentiable Programming".

Complete solutions to the Programming Massively Parallel Processors Edition 4

Summary, Code for Deep Neural Network Quantization