Python Gpu-computing Resources

Manipulation of 3D Models Using Hand Gesture This program allows user to manipulation 3D models (.obj format) with their hands. The project support bo

Transformer in Triton (wip) Implementation of a Transformer, but completely in Triton. I'm completely new to lower-level neural net code, so this repo

CloudComputingCourse Material related to the Principles of Cloud Computing course. This repository comprises material that I use to teach my Principle

PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network.

Medical image preprocessing and augmentation toolkit for deep learning. Part of the PyTorch Ecosystem.

WarpDrive is a flexible, lightweight, and easy-to-use open-source reinforcement learning (RL) framework that implements end-to-end multi-agent RL on a single GPU (Graphics Processing Unit).

NEWLY ADDED A3G A NEW GPU/CPU ARCHITECTURE OF A3C FOR SUBSTANTIALLY ACCELERATED TRAINING!! RL A3C Pytorch NEWLY ADDED A3G!! New implementation of A3C

A deep learning library for spiking neural networks. Norse aims to exploit the advantages of bio-inspired neural components, which are sparse and even

Framework overview This library allows to quickly implement different architectures based on Reservoir Computing (the family of approaches popularized

Note: This is an alpha (preview) version which is still under refining. nn-Meter is a novel and efficient system to accurately predict the inference l

A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.

Gradient Cache Gradient Cache is a simple technique for unlimitedly scaling contrastive learning batch far beyond GPU memory constraint. This means tr

ParallelFold Author: Bozitao Zhong This is a modified version of DeepMind's Alphafold2 to divide CPU part (MSA and template searching) and GPU part (p

Demo BERT ONNX pipeline written in rust This demo showcase the use of onnxruntime-rs with a GPU on CUDA 11 to run Bert in a data pipeline with Rust. R

PyTorch Large-Scale Language Model A Large-Scale PyTorch Language Model trained on the 1-Billion Word (LM1B) / (GBW) dataset Latest Results 39.98 Perp

GPU-accelerated PyTorch implementation of Zero-shot User Intent Detection via Capsule Neural Networks This repository implements a capsule model Inten

​ DS2.ai is an integrated AI operation solution that supports all stages from custom AI development to deployment. It is an AI-specialized platform service that collects data, builds a training dataset through data labeling, and enables automatic development of artificial intelligence and easy deployment and operation.

Py2CUDA Convert python code to CUDA. Usage To convert a python file say named py_file.py to CUDA, run python generate_cuda.py --file py_file.py --arch

Deep Learning Winter School, November 2107. Tel Aviv Deep Learning Bootcamp : http://deep-ml.com. About Tel-Aviv Deep Learning Bootcamp is an intensiv

The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

MentisOculi Pytorch Path Tracer A very simple and small path tracer written in pytorch meant to be run on the GPU Why use pytorch and not some other c

ocaml-torch provides some ocaml bindings for the PyTorch tensor library. This brings to OCaml NumPy-like tensor computations with GPU acceleration and tape-based automatic differentiation.

All-in-one web-based development environment for machine learning Getting Started • Features & Screenshots • Support • Report a Bug • FAQ • Known Issu

XGBoost-Ray is a distributed backend for XGBoost, built on top of distributed computing framework Ray.

This is my reading list for my PhD in AI, NLP, Deep Learning and more.

QPT - Quick packaging tool 快捷封装工具 GitHub主页 | Gitee主页 QPT是一款可以“模拟”开发环境的多功能封装工具，一行命令即可将普通的Python脚本打包成EXE可执行程序，与此同时还可轻松引入CUDA等深度学习加速库， 尽可能在用户使用时复现您的开发环境。

U Net Lowered with Keras Complete U-net Implementation with keras Original Paper Link : https://arxiv.org/abs/1505.04597 Special Implementations : The

What is nnDetection? Simultaneous localisation and categorization of objects in medical images, also referred to as medical object detection, is of hi

PyTorch code to reproduce LyDROO algorithm [1], which is an online computation offloading algorithm to maximize the network data processing capability subject to the long-term data queue stability and average power constraints. It applies Lyapunov optimization to decouple the multi-stage stochastic MINLP into deterministic per-frame MINLP subproblems and solves each subproblem via DROO algorithm. It includes:

DistML is a Ray extension library to support large-scale distributed ML training on heterogeneous multi-node multi-GPU clusters

websocket-for-data-transmission This websocket program is for data transmission between server and client. Data transmission is for Federated Learning

Newegg Shuffle Python module(s) to help you with the Newegg raffle How to use $ git clone https://github.com/Matthew17-21/Newegg-Shuffle $ cd Newegg-S

Habitat: A Runtime-Based Computational Performance Predictor for Deep Neural Network Training Habitat is a tool that predicts a deep neural network's

An interactive NVIDIA-GPU process viewer, the one-stop solution for GPU process management.

A lightweight (serverless) native python parallel processing framework based on simple decorators and call graphs, supporting both control flow and dataflow execution paradigms as well as de-centralized CPU & GPU scheduling.

AWS Data Engineering Pipeline This is a repository for the Duke University Cloud Computing course project on Serverless Data Engineering Pipeline. For

Discord Bot that leverages the idea of nested containers using podman, runs untrusted user input, executes Quantum Circuits, allows users to refer to the Qiskit Documentation, and provides the ability to search questions on the Quantum Computing StackExchange.

GeoDoodle Geodesic distance computation for Blender meshes Table of Contents Overivew Usage Implementation Overview This addon provides an operator fo

python_graphs This package is for computing graph representations of Python programs for machine learning applications. It includes the following modu

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

Efficient implementations of Product Quantization and its variants using Pytorch and CUDA

🤗 Accelerate was created for PyTorch users who like to write the training loop of PyTorch models but are reluctant to write and maintain the boilerplate code needed to use multi-GPUs/TPU/fp16.

This repo contains a selection of projects designed to help you learn the basics of computer graphics. We'll be writing shaders to render interactive two-dimensional and three-dimensional scenes.

xitorch is a PyTorch-based library of differentiable functions and functionals that can be widely used in scientific computing applications as well as deep learning.

[Open Source]. The improved version of AnimeGAN. Landscape photos/videos to anime

InfoPro-Pytorch The Information Propagation algorithm for training deep networks with local supervision. (ICLR 2021) Revisiting Locally Supervised Lea

monolish is a linear equation solver library that monolithically fuses variable data type, matrix structures, matrix data format, vendor specific data transfer APIs, and vendor specific numerical algebra libraries.

An open-source library of algorithms to analyse time series in GPU and CPU.

IPython: Productive Interactive Computing Overview Welcome to IPython. Our full documentation is available on ipython.readthedocs.io and contains info

Guide: Finetune GPT2-XL (1.5 Billion Parameters) and GPT-NEO (2.7 Billion Parameters) on a single 16 GB VRAM V100 Google Cloud instance with Huggingfa

GPyTorch GPyTorch is a Gaussian process library implemented using PyTorch. GPyTorch is designed for creating scalable, flexible, and modular Gaussian

PyTorch Implementation of Differentiable SDE Solvers This library provides stochastic differential equation (SDE) solvers with GPU support and efficie

PyTorch Implementation of Differentiable ODE Solvers This library provides ordinary differential equation (ODE) solvers implemented in PyTorch. Backpr

ipyexperiments jupyter/ipython experiment containers and utils for profiling and reclaiming GPU and general RAM, and detecting memory leaks. About Thi

SpeedTorch Faster pinned CPU tensor - GPU Pytorch variabe transfer and GPU tensor - GPU Pytorch variable transfer, in certain cases. Update 9-29-1

GPUtil GPUtil is a Python module for getting the GPU status from NVIDA GPUs using nvidia-smi. GPUtil locates all GPUs on the computer, determines thei

Vulkan Kompute The general purpose GPU compute framework for cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabl

A lightweight, GPU accelerated, SQL engine built on the RAPIDS.ai ecosystem. Get Started on app.blazingsql.com Getting Started | Documentation | Examp

cuML - GPU Machine Learning Algorithms cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions t

NVIDIA DALI The NVIDIA Data Loading Library (DALI) is a library for data loading and pre-processing to accelerate deep learning applications. It provi

py3nvml Documentation also available at readthedocs. Python 3 compatible bindings to the NVIDIA Management Library. Can be used to query the state of

cuDF - GPU DataFrames NOTE: For the latest stable README.md ensure you are on the main branch. Resources cuDF Reference Documentation: Python API refe

Package Description scikit-cuda provides Python interfaces to many of the functions in the CUDA device/runtime, CUBLAS, CUFFT, and CUSOLVER libraries

ArrayFire is a general-purpose library that simplifies the process of developing software that targets parallel and massively-parallel architectures i

PyCUDA lets you access Nvidia's CUDA parallel computation API from Python. Several wrappers of the CUDA API already exist-so what's so special about P

gpustat Just less than nvidia-smi? NOTE: This works with NVIDIA Graphics Devices only, no AMD support as of now. Contributions are welcome! Self-Promo

CuPy : A NumPy-compatible array library accelerated by CUDA Website | Docs | Install Guide | Tutorial | Examples | API Reference | Forum CuPy is an im

🎛 lazycluster Distributed machine learning made simple. Use your preferred distributed ML framework like a lazy engineer. Getting Started • Highlight

Hivemind: decentralized deep learning in PyTorch Hivemind is a PyTorch library to train large neural networks across the Internet. Its intended usage

Project Home Blog Documents Paper Media Coverage Join Fiber users email list [email protected] Fiber Distributed Computing for AI Made Simp

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. 10x Larger Models 10x Faster Trainin

MPI for Python Overview Welcome to MPI for Python. This package provides Python bindings for the Message Passing Interface (MPI) standard. It is imple

Elephas: Distributed Deep Learning with Keras & Spark Elephas is an extension of Keras, which allows you to run distributed deep learning models at sc

Interactive Parallel Computing with IPython ipyparallel is the new home of IPython.parallel. ipyparallel is a Python package and collection of CLI scr

Our article on Towards Data Science introduces the package and provides background information. Pytorch Forecasting aims to ease state-of-the-art time

STUMPY STUMPY is a powerful and scalable library that efficiently computes something called the matrix profile, which can be used for a variety of tim

TF Quant Finance: TensorFlow based Quant Finance Library Table of contents Introduction Installation TensorFlow training Development roadmap Examples

⚠️ The Nimbus infrastructure project is no longer under development. ⚠️ For more information, please read the news announcement. If you are interested

Spack Spack is a multi-platform package manager that builds and installs multiple versions and configurations of software. It works on Linux, macOS, a

Tensorflow 2 Object Detection API Bu tutorial, TensorFlow 2.x'in kararlı sürümü olan TensorFlow 2.3'ye yöneliktir. Bu, görüntülerde / videoda nesne a

Scikit-Optimize Scikit-Optimize, or skopt, is a simple and efficient library to minimize (very) expensive and noisy black-box functions. It implements

Karoo GP Karoo GP is an evolutionary algorithm, a genetic programming application suite written in Python which supports both symbolic regression and

GPyTorch GPyTorch is a Gaussian process library implemented using PyTorch. GPyTorch is designed for creating scalable, flexible, and modular Gaussian

swifter A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner. Blog posts Release 1.0.0 Fir

cuDF - GPU DataFrames NOTE: For the latest stable README.md ensure you are on the main branch. Built based on the Apache Arrow columnar memory format,

Elephas: Distributed Deep Learning with Keras & Spark Elephas is an extension of Keras, which allows you to run distributed deep learning models at sc

Documentations | Installation | Parameters | Python (scikit-learn) interface What's new? ThunderGBM won 2019 Best Paper Award from IEEE Transactions o

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

What's new We have recently released ThunderGBM, a fast GBDT and Random Forest library on GPUs. add scikit-learn interface, see here Overview The miss

pyGAM Generalized Additive Models in Python. Documentation Official pyGAM Documentation: Read the Docs Building interpretable models with Generalized

[Due to the time taken @ uni, work + hell breaking loose in my life, since things have calmed down a bit, will continue commiting!!!] [By the way, I'm

Sparkit-learn PySpark + Scikit-learn = Sparkit-learn GitHub: https://github.com/lensacom/sparkit-learn About Sparkit-learn aims to provide scikit-lear

cuML - GPU Machine Learning Algorithms cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions t

Spack Spack is a multi-platform package manager that builds and installs multiple versions and configurations of software. It works on Linux, macOS, a

ReproZip ReproZip is a tool aimed at simplifying the process of creating reproducible experiments from command-line executions, a frequently-used comm

Smart Social Distancing Smart Social Distancing Introduction Getting Started Prerequisites Usage Processor Optional Parameters Configuring AWS credent

lazyprofiler Lazy Profiler is a simple utility to collect CPU, GPU, RAM and GPU Memory stats while the program is running. Installation Use the packag

Dash Dash is the most downloaded, trusted Python framework for building ML & data science web apps. Built on top of Plotly.js, React and Flask, Dash t

Project DeepSpeech DeepSpeech is an open-source Speech-To-Text engine, using a model trained by machine learning techniques based on Baidu's Deep Spee

MDCT A fast MDCT implementation using SciPy and FFTs Installation As usual pip install mdct Dependencies NumPy SciPy STFT Usage import mdct spectrum