Top 20 NuGet cuda Packages
A complete C# re-write of Berkeley's open source Convolutional Architecture for Fast Feature Encoding (CAFFE) for Windows C# Developers with full On-line Help, now with GPT, Seq2Seq/Attention, Single-Shot MultiBox, TripletNet, SiameseNet, NoisyNet, Deep Q-Network and Policy Gradient Reinforcement Le...
ILGPU compiler and runtime library for convenient and high-performance GPU programming in .Net. Samples can be found in the GitHub repository: https://github.com/m4rs-mt/ILGPU/tree/master/Samples
Giving Windows C# developers easy access to the ONNX AI Model Format for easy model conversions.
Tensor (n-dimensional array) library for F# Core features: - n-dimensional arrays (tensors) in host memory or on CUDA GPUs - element-wise operations (addition, multiplication, absolute value, etc.) - basic linear algebra operations (dot product, SVD decomposition, mat...
A TensorFlow-inspired neural network library built from scratch in C# 7.3 for .NET Standard 2.0, with GPU support through cuDNN and native memory management
ILGPU Algorithms library for high-level GPU programming. Samples can be found in the GitHub repository: https://github.com/m4rs-mt/ILGPU/tree/master/Samples
Alea GPU Platform core. It provides kernel constructs and a JIT compiler that translates IL instructions or F# quotations into GPU kernels. For more details, please go to http://www.quantalea.com .
Based on ManagedCuda-11 + CudaBlas + NVRTC, which aims an easy integration of NVidia's CUDA in .net applications written in C#, Visual Basic or any other .net language. This package includes only the core managedCuda library, no additional CUDA libraries and is platform independent (Windows/Linux/.n...
Bright Wire CUDA adds GPU support to Bright Wire. This lets you run Bright Wire machine learning on a Maxwell or better NVIDIA GPU.
This is the .net standard 2 version of BrightWire.CUDA which adds CUDA support to Bright Wire. This lets you run Bright Wire machine learning on a Maxwell or better NVIDIA GPU (x64 only).
Library for general purpose numerical computing and Machine Learning based on tensors and tensor expressions.
A compiler, runtime, and API for GP-GPU computing using C# or any other NET language, for Windows and Ubuntu x64.