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Book: Quantum Computing Architecture and Hardware for Engineers - Step by Step
DirectML is a high-performance, hardware-accelerated DirectX 12 library for machine learning. DirectML provides GPU acceleration for common machine learning tasks across a broad range of supported …
Class Slides for Introduction to Quantum Computing
Advanced User-Programmed Calibration Software for Large-Scale Quantum Computers
Home for cuQuantum Python & NVIDIA cuQuantum SDK C++ samples
C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows
Accelerated libraries for quantum-classical computing built on CUDA-Q.
An awesome list of helpful resources for students learning MATLAB & Simulink. List includes tips & tricks, tutorials, videos, cheat sheets, and opportunities to learn MATLAB & Simulink.
Research presentations, lectures, tutorials, and technical notes by Dr. Zlatko K. Minev
Getting Started with LabVIEW 3 hour Session Raspberry Pi Pico HW English
Source code for the TKET quantum compiler, Python bindings and utilities
Fullstack app framework for web, desktop, mobile, and more.
QML repo collecting scripts of image classification realzied via parametrized quantum circuits and quantum neural networks.
In this work, we use LR-QAOA protocol as an easy-to-implement scalable benchmarking methodology that assesses quantum process units (QPUs) at different widths (number of qubits) and 2-qubit gate de…
Image inpainting tool powered by SOTA AI Model. Remove any unwanted object, defect, people from your pictures or erase and replace(powered by stable diffusion) any thing on your pictures.
What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
A list of developer portfolios for your inspiration
Notes for COMP 458 (Spring 2025): Quantum Computing Algorithms 🧬
This workshop provides an introduction to Quantum Machine Learning using PennyLane and PyTorch, with hands-on exercises and take-home challenges. The workshop includes four practical sessions that …
Design automation software tools for Topological Quantum Error Correction
This repo contains CUDA-Q Academic materials, including self-paced Jupyter notebook modules for building and optimizing hybrid quantum-classical algorithms using CUDA-Q.