Displaying 1 to 20 from 106 results

nnvm - Bring deep learning to bare metal

  •    C++

The following code snippet demonstrates the general workflow of nnvm compiler.Licensed under an Apache-2.0 license.

nvidia-docker - Build and run Docker containers leveraging NVIDIA GPUs

  •    Makefile

The full documentation and frequently asked questions are available on the repository wiki. An introduction to the NVIDIA Container Runtime is also covered in our blog post.

chainer - A flexible framework of neural networks for deep learning

  •    Python

Chainer is a Python-based deep learning framework aiming at flexibility. It provides automatic differentiation APIs based on the define-by-run approach (a.k.a. dynamic computational graphs) as well as object-oriented high-level APIs to build and train neural networks. It also supports CUDA/cuDNN using CuPy for high performance training and inference. For more details of Chainer, see the documents and resources listed above and join the community in Forum, Slack, and Twitter. The stable version of current Chainer is separated in here: v3.

cupy - NumPy-like API accelerated with CUDA

  •    Python

CuPy is an implementation of NumPy-compatible multi-dimensional array on CUDA. CuPy consists of the core multi-dimensional array class, cupy.ndarray, and many functions on it. It supports a subset of numpy.ndarray interface. For detailed instructions on installing CuPy, see the installation guide.




Deep-Learning-Boot-Camp - A community run, 5-day PyTorch Deep Learning Bootcamp

  •    Jupyter

Tel-Aviv Deep Learning Bootcamp is an intensive (and free!) 5-day program intended to teach you all about deep learning. It is nonprofit focused on advancing data science education and fostering entrepreneurship. The Bootcamp is a prominent venue for graduate students, researchers, and data science professionals. It offers a chance to study the essential and innovative aspects of deep learning. Participation is via a donation to the A.L.S ASSOCIATION for promoting research of the Amyotrophic Lateral Sclerosis (ALS) disease.

Deep-learning-with-cats - Deep learning with cats (^._.^)

  •    Python

Discussion of the results at https://ajolicoeur.wordpress.com/cats.

Remotery - Single C file, Realtime CPU/GPU Profiler with Remote Web Viewer

  •    C

A realtime CPU/GPU profiler hosted in a single C file with a viewer that runs in a web browser. Windows (MSVC) - add lib/Remotery.c and lib/Remotery.h to your program. Set include directories to add Remotery/lib path. The required library ws2_32.lib should be picked up through the use of the #pragma comment(lib, "ws2_32.lib") directive in Remotery.c.

scikit-cuda - Python interface to GPU-powered libraries

  •    Python

scikit-cuda provides Python interfaces to many of the functions in the CUDA device/runtime, CUBLAS, CUFFT, and CUSOLVER libraries distributed as part of NVIDIA's CUDA Programming Toolkit, as well as interfaces to select functions in the CULA Dense Toolkit. Both low-level wrapper functions similar to their C counterparts and high-level functions comparable to those in NumPy and Scipy are provided. Package documentation is available at http://scikit-cuda.readthedocs.org/. Many of the high-level functions have examples in their docstrings. More illustrations of how to use both the wrappers and high-level functions can be found in the demos/ and tests/ subdirectories.


accelerate - Embedded language for high-performance array computations

  •    Haskell

Data.Array.Accelerate defines an embedded language of array computations for high-performance computing in Haskell. Computations on multi-dimensional, regular arrays are expressed in the form of parameterised collective operations (such as maps, reductions, and permutations). These computations are online-compiled and executed on a range of architectures. Chapter 6 of Simon Marlow's book Parallel and Concurrent Programming in Haskell contains a tutorial introduction to Accelerate.

ArrayFire - Parallel Computing Library

  •    C++

ArrayFire is a high performance software library for parallel computing with an easy-to-use API. Its array based function set makes parallel programming simple. ArrayFire's multiple backends (CUDA, OpenCL and native CPU) make it platform independent and highly portable. A few lines of code in ArrayFire can replace dozens of lines of parallel computing code, saving you valuable time and lowering development costs.

neanderthal - Fast Clojure Matrix Library

  •    Clojure

Neanderthal is a Clojure library for fast matrix and linear algebra computations based on the highly optimized native libraries of BLAS and LAPACK computation routines for both CPU and GPU.. Read the documentation at Neanderthal Web Site.

vexcl - VexCL is a C++ vector expression template library for OpenCL/CUDA

  •    C++

VexCL is a vector expression template library for OpenCL/CUDA. It has been created for ease of GPGPU development with C++. VexCL strives to reduce amount of boilerplate code needed to develop GPGPU applications. The library provides convenient and intuitive notation for vector arithmetic, reduction, sparse matrix-vector products, etc. Multi-device and even multi-platform computations are supported. The source code of the library is distributed under very permissive MIT license.

kmcuda - Large scale K-means and K-nn implementation on NVIDIA GPU / CUDA

  •    Jupyter

K-means implementation is based on "Yinyang K-Means: A Drop-In Replacement of the Classic K-Means with Consistent Speedup". While it introduces some overhead and many conditional clauses which are bad for CUDA, it still shows 1.6-2x speedup against the Lloyd algorithm. K-nearest neighbors employ the same triangle inequality idea and require precalculated centroids and cluster assignments, similar to the flattened ball tree. Technically, this project is a shared library which exports two functions defined in kmcuda.h: kmeans_cuda and knn_cuda. It has built-in Python3 and R native extension support, so you can from libKMCUDA import kmeans_cuda or dyn.load("libKMCUDA.so").

gunrock - High-Performance Graph Primitives on GPUs

  •    Cuda

Gunrock is a CUDA library for graph-processing designed specifically for the GPU. It uses a high-level, bulk-synchronous, data-centric abstraction focused on operations on a vertex or edge frontier. Gunrock achieves a balance between performance and expressiveness by coupling high performance GPU computing primitives and optimization strategies with a high-level programming model that allows programmers to quickly develop new graph primitives with small code size and minimal GPU programming knowledge. For more details, please visit our website, read Why Gunrock, our TOPC 2017 paper Gunrock: GPU Graph Analytics, look at our results, and find more details in our publications. See Release Notes to keep up with the our latest changes.

xmrig-nvidia - Monero (XMR) NVIDIA miner

  •    C++

⚠️ You must update miners to version 2.5 before April 6 due Monero PoW change. XMRig is high performance Monero (XMR) NVIDIA miner, with the official full Windows support.

dockerfiles - Compilation of Dockerfiles with automated builds enabled on the Docker Registry

  •    Dockerfile

Compilation of Dockerfiles with automated builds enabled on the Docker Hub. Not suitable for production environments. These images are under continuous development, so breaking changes may be introduced. Nearly all images are based on Ubuntu Core 14.04 LTS, built with minimising size/layers and best practices in mind. Dependencies are indicated left to right e.g. cuda-vnc is VNC built on top of CUDA. Explicit dependencies are excluded.

CuBLAS.Net

  •    

A wrapper for NVidia's CuBLAS (Compute Unified Basic Linear Algebra Subprograms) for the CLR.

FsGPU

  •    

FsGPU project contains library and samples to assist general purpose GPU programming in F# for CUDA enabled devices.

managedCUDA

  •    DotNet

managedCUDA makes the CUDA Driver API available in .net applications written in C#, Visual Basic or any other .net language. It also includes classes for an easy handling and interop with CUDA, i.e. build-in CUDA types like float3.

Optix.NET

  •    DotNet

Optix.NET is a .NET wrapper for the Nvidia Optix GPU ray-tracing library.