A high-performance, zero-overhead, extensible Python compiler with built-in NumPy support
-
Updated
Aug 11, 2025 - Python
A high-performance, zero-overhead, extensible Python compiler with built-in NumPy support
Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals
Computations and statistics on manifolds with geometric structures.
Implementation of a Transformer, but completely in Triton
Scientific Computing in Python with Mojo and MAX acceleration
Fast deterministic all-Python Lennard-Jones particle simulator that utilizes Numba for GPU-accelerated computation.
Set up ML profiling in 60 seconds
Implementation of the Apriori and Eclat algorithms, two of the best-known basic algorithms for mining frequent item sets in a set of transactions, implementation in Python.
Boilerplate for GPU-Accelerated TensorFlow and PyTorch code on M1 Macbook
🌟 Vertex Centric approach for building GNN/TGNNs
pyCUDA implementation of forward propagation for Convolutional Neural Networks
Fundamentals of heterogeneous parallel programming with CUDA C/C++ at the beginner level.
bilibili视频【CUDA 12.x 并行编程入门(Python版)】配套代码
vgg16 inference implementation using tensorflow, numpy and pycuda
A package to run commands when GPU resources are available
A helper package to easily time Numba CUDA GPU events ⌛
Simplify GPU Setup: Drivers, CUDA, Frameworks, and more!
Advanced environmental monitoring platform combining computer vision and geospatial analysis. Low-compute cloud detection, 3D terrain visualization from GeoTIFF data, multi-camera calibration, and statistical validation. scalable architecture with Flask web interface and SQLite backend.
Real-time object detection app using YOLOv5/YOLOv8 with custom UI built from scratch using Pyglet & OpenGL. UI animations made in Adobe After Effects, rendered as GIFs, and integrated via uxElements.py. Multi-core processing enables live capture, detection, and display with low latency. Uses Open Images v7 dataset. Train mode is WIP.
CUDA accelerated raytracer using PyCUDA in Python
Add a description, image, and links to the gpu-programming topic page so that developers can more easily learn about it.
To associate your repository with the gpu-programming topic, visit your repo's landing page and select "manage topics."