Tensors and Dynamic neural networks in Python with strong GPU acceleration
- neural-network
- autograd
- gpu
- numpy
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Tensors and Dynamic neural networks in Python with strong GPU acceleration
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
The fastai deep learning library
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Burn is a next generation tensor library and Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.
🤖 GPU accelerated Neural networks in JavaScript for Browsers and Node.js
Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learn...
NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.
Solve puzzles. Learn CUDA.
NumPy & SciPy for GPU
The Triton Inference Server provides an optimized cloud and edge inferencing solution.
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High-performance GPGPU inference of OpenAI's Whisper automatic speech recognition (ASR) model
CUDA Templates and Python DSLs for High-Performance Linear Algebra
cuDF - GPU DataFrame Library
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
High-performance TensorFlow library for quantitative finance.
NVIDIA cuML: GPU-Accelerated Machine Learning
Optimized primitives for collective multi-GPU communication
Run Keras models in the browser, with GPU support using WebGL