ChainerA flexible framework of neural networks for deep learning
Stars: ✭ 5,656 (+5853.68%)
CupyNumPy & SciPy for GPU
Stars: ✭ 5,625 (+5821.05%)
SpeedtorchLibrary for faster pinned CPU <-> GPU transfer in Pytorch
Stars: ✭ 615 (+547.37%)
CaerHigh-performance Vision library in Python. Scale your research, not boilerplate.
Stars: ✭ 452 (+375.79%)
BohriumAutomatic parallelization of Python/NumPy, C, and C++ codes on Linux and MacOSX
Stars: ✭ 209 (+120%)
CudfcuDF - GPU DataFrame Library
Stars: ✭ 4,370 (+4500%)
Open3dOpen3D: A Modern Library for 3D Data Processing
Stars: ✭ 5,860 (+6068.42%)
ThundersvmThunderSVM: A Fast SVM Library on GPUs and CPUs
Stars: ✭ 1,282 (+1249.47%)
CudasiftA CUDA implementation of SIFT for NVidia GPUs (1.2 ms on a GTX 1060)
Stars: ✭ 555 (+484.21%)
ThundergbmThunderGBM: Fast GBDTs and Random Forests on GPUs
Stars: ✭ 586 (+516.84%)
MarianFast Neural Machine Translation in C++
Stars: ✭ 777 (+717.89%)
NumerNumeric Erlang - vector and matrix operations with CUDA. Heavily inspired by Pteracuda - https://github.com/kevsmith/pteracuda
Stars: ✭ 91 (-4.21%)
Cuda.jlCUDA programming in Julia.
Stars: ✭ 370 (+289.47%)
IlgpuILGPU JIT Compiler for high-performance .Net GPU programs
Stars: ✭ 374 (+293.68%)
H2o4gpuH2Oai GPU Edition
Stars: ✭ 416 (+337.89%)
MegengineMegEngine 是一个快速、可拓展、易于使用且支持自动求导的深度学习框架
Stars: ✭ 4,081 (+4195.79%)
Stdgpustdgpu: Efficient STL-like Data Structures on the GPU
Stars: ✭ 531 (+458.95%)
Lighthouse2Lighthouse 2 framework for real-time ray tracing
Stars: ✭ 542 (+470.53%)
GunrockHigh-Performance Graph Primitives on GPUs
Stars: ✭ 718 (+655.79%)
NumbaNumPy aware dynamic Python compiler using LLVM
Stars: ✭ 7,090 (+7363.16%)
GraphviteGraphVite: A General and High-performance Graph Embedding System
Stars: ✭ 865 (+810.53%)
CubCooperative primitives for CUDA C++.
Stars: ✭ 883 (+829.47%)
DrlkitA High Level Python Deep Reinforcement Learning library. Great for beginners, prototyping and quickly comparing algorithms
Stars: ✭ 29 (-69.47%)
Nvidia libs testTests and benchmarks for cudnn (and in the future, other nvidia libraries)
Stars: ✭ 36 (-62.11%)
CudaExperiments with CUDA and Rust
Stars: ✭ 31 (-67.37%)
Qualia2.0Qualia is a deep learning framework deeply integrated with automatic differentiation and dynamic graphing with CUDA acceleration. Qualia was built from scratch.
Stars: ✭ 41 (-56.84%)
Cuda Api WrappersThin C++-flavored wrappers for the CUDA Runtime API
Stars: ✭ 362 (+281.05%)
Arrayfire PythonPython bindings for ArrayFire: A general purpose GPU library.
Stars: ✭ 358 (+276.84%)
HipsyclImplementation of SYCL for CPUs, AMD GPUs, NVIDIA GPUs
Stars: ✭ 377 (+296.84%)
BayaderaHigh-performance Bayesian Data Analysis on the GPU in Clojure
Stars: ✭ 342 (+260%)
Pytorch Pwc a reimplementation of PWC-Net in PyTorch that matches the official Caffe version
Stars: ✭ 402 (+323.16%)
Gpuvideo AndroidThis library apply video filter on generate an Mp4 and on ExoPlayer video and Video Recording with Camera2.
Stars: ✭ 403 (+324.21%)
MprReference implementation for "Massively Parallel Rendering of Complex Closed-Form Implicit Surfaces" (SIGGRAPH 2020)
Stars: ✭ 84 (-11.58%)
ArrayfireArrayFire: a general purpose GPU library.
Stars: ✭ 3,693 (+3787.37%)
RustacudaRusty wrapper for the CUDA Driver API
Stars: ✭ 511 (+437.89%)
BitcrackerBitCracker is the first open source password cracking tool for memory units encrypted with BitLocker
Stars: ✭ 463 (+387.37%)
PycudaCUDA integration for Python, plus shiny features
Stars: ✭ 1,112 (+1070.53%)
Tsne CudaGPU Accelerated t-SNE for CUDA with Python bindings
Stars: ✭ 1,120 (+1078.95%)
Deeppipe2Deep Learning library using GPU(CUDA/cuBLAS)
Stars: ✭ 90 (-5.26%)
ThrustThe C++ parallel algorithms library.
Stars: ✭ 3,595 (+3684.21%)
NeanderthalFast Clojure Matrix Library
Stars: ✭ 927 (+875.79%)
Sepconv Slomoan implementation of Video Frame Interpolation via Adaptive Separable Convolution using PyTorch
Stars: ✭ 918 (+866.32%)
MetalpetalA GPU accelerated image and video processing framework built on Metal.
Stars: ✭ 907 (+854.74%)
WheelsPerformance-optimized wheels for TensorFlow (SSE, AVX, FMA, XLA, MPI)
Stars: ✭ 891 (+837.89%)
Cuda Design PatternsSome CUDA design patterns and a bit of template magic for CUDA
Stars: ✭ 78 (-17.89%)
TensorlyTensorLy: Tensor Learning in Python.
Stars: ✭ 977 (+928.42%)
Carlsim3CARLsim is an efficient, easy-to-use, GPU-accelerated software framework for simulating large-scale spiking neural network (SNN) models with a high degree of biological detail.
Stars: ✭ 52 (-45.26%)
Scikit CudaPython interface to GPU-powered libraries
Stars: ✭ 803 (+745.26%)
DokaiCollection of Docker images for ML/DL and video processing projects
Stars: ✭ 58 (-38.95%)
GgnnGGNN: State of the Art Graph-based GPU Nearest Neighbor Search
Stars: ✭ 63 (-33.68%)
HeteroflowConcurrent CPU-GPU Programming using Task Models
Stars: ✭ 57 (-40%)
ParenchymaAn extensible HPC framework for CUDA, OpenCL and native CPU.
Stars: ✭ 71 (-25.26%)
GdrlGrokking Deep Reinforcement Learning
Stars: ✭ 304 (+220%)
Fast gicpA collection of GICP-based fast point cloud registration algorithms
Stars: ✭ 307 (+223.16%)
PyopenclOpenCL integration for Python, plus shiny features
Stars: ✭ 790 (+731.58%)
3d Ken Burnsan implementation of 3D Ken Burns Effect from a Single Image using PyTorch
Stars: ✭ 1,073 (+1029.47%)
ArboretumGradient Boosting powered by GPU(NVIDIA CUDA)
Stars: ✭ 64 (-32.63%)