JetsonHelmut Hoffer von Ankershoffen experimenting with arm64 based NVIDIA Jetson (Nano and AGX Xavier) edge devices running Kubernetes (K8s) for machine learning (ML) including Jupyter Notebooks, TensorFlow Training and TensorFlow Serving using CUDA for smart IoT.
GinkgoNumerical linear algebra software package
Cuda CnnCNN accelerated by cuda. Test on mnist and finilly get 99.76%
SketchgraphsA dataset of 15 million CAD sketches with geometric constraint graphs.
GpurirPython library for Room Impulse Response (RIR) simulation with GPU acceleration
RemoterySingle C file, Realtime CPU/GPU Profiler with Remote Web Viewer
Hoomd BlueMolecular dynamics and Monte Carlo soft matter simulation on GPUs.
Libgdf[ARCHIVED] C GPU DataFrame Library
ForwardA library for high performance deep learning inference on NVIDIA GPUs.
NsimdAgenium Scale vectorization library for CPUs and GPUs
Marian DevFast Neural Machine Translation in C++ - development repository
SpanetSpatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset (CVPR'19)
Partial Order PruningPartial Order Pruning: for Best Speed/Accuracy Trade-off in Neural Architecture Search
NnvmNo description or website provided.
LibcudacxxThe C++ Standard Library for your entire system.
MixbenchA GPU benchmark tool for evaluating GPUs on mixed operational intensity kernels (CUDA, OpenCL, HIP, SYCL)
AgencyExecution primitives for C++
Kaldikaldi-asr/kaldi is the official location of the Kaldi project.
OnemkloneAPI Math Kernel Library (oneMKL) Interfaces
BabelstreamSTREAM, for lots of devices written in many programming models
Knn cudaFast K-Nearest Neighbor search with GPU
SpocStream Processing with OCaml
MtensorA C++ Cuda Tensor Lazy Computing Library
CltuneCLTune: An automatic OpenCL & CUDA kernel tuner
Pytorch spnExtension package for spatial propagation network in pytorch.
Tensorflow Object Detection TutorialThe purpose of this tutorial is to learn how to install and prepare TensorFlow framework to train your own convolutional neural network object detection classifier for multiple objects, starting from scratch
Pytorch Unflow a reimplementation of UnFlow in PyTorch that matches the official TensorFlow version
Adacof PytorchOfficial source code for our paper "AdaCoF: Adaptive Collaboration of Flows for Video Frame Interpolation" (CVPR 2020)
Futhark💥💻💥 A data-parallel functional programming language
CuheCUDA Homomorphic Encryption Library
HashcatWorld's fastest and most advanced password recovery utility
DaceDaCe - Data Centric Parallel Programming
PygraphistryPyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer
DeepnetDeep.Net machine learning framework for F#
DppDetail-Preserving Pooling in Deep Networks (CVPR 2018)
SupraSUPRA: Software Defined Ultrasound Processing for Real-Time Applications - An Open Source 2D and 3D Pipeline from Beamforming to B-Mode
PynvvlA Python wrapper of NVIDIA Video Loader (NVVL) with CuPy for fast video loading with Python
Region ConvNot All Pixels Are Equal: Difficulty-Aware Semantic Segmentation via Deep Layer Cascade
Fbtt EmbeddingThis is a Tensor Train based compression library to compress sparse embedding tables used in large-scale machine learning models such as recommendation and natural language processing. We showed this library can reduce the total model size by up to 100x in Facebook’s open sourced DLRM model while achieving same model quality. Our implementation is faster than the state-of-the-art implementations. Existing the state-of-the-art library also decompresses the whole embedding tables on the fly therefore they do not provide memory reduction during runtime of the training. Our library decompresses only the requested rows therefore can provide 10,000 times memory footprint reduction per embedding table. The library also includes a software cache to store a portion of the entries in the table in decompressed format for faster lookup and process.
NumerNumeric Erlang - vector and matrix operations with CUDA. Heavily inspired by Pteracuda - https://github.com/kevsmith/pteracuda
AuroraMinimal Deep Learning library is written in Python/Cython/C++ and Numpy/CUDA/cuDNN.