CudaControl 1.12.2.41

.NET Framework 4.0 This package targets .NET Framework 4.0. The package is compatible with this framework or higher. 
dotnet add package CudaControl --version 1.12.2.41
                    


                    

                
NuGet\Install-Package CudaControl -Version 1.12.2.41
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package. 
<PackageReference Include="CudaControl" Version="1.12.2.41" />
For projects that support PackageReference, copy this XML node into the project file to reference the package. 
<PackageVersion Include="CudaControl" Version="1.12.2.41" />
                    


                            Directory.Packages.props
                        

                    

                
<PackageReference Include="CudaControl" />
                    


                            Project file
For projects that support Central Package Management (CPM), copy this XML node into the solution Directory.Packages.props file to version the package. 
paket add CudaControl --version 1.12.2.41
                    


                    

                
#r "nuget: CudaControl, 1.12.2.41"
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package. 
#addin nuget:?package=CudaControl&version=1.12.2.41
                    


                            Install as a Cake Addin
                        

                    

                
#tool nuget:?package=CudaControl&version=1.12.2.41
                    


                            Install as a Cake Tool

This release has the following new additions: • Windows 11 22H2, OS Build 22612.2283 • Windows 10 22H2, OS Build 19045.3448, SDK 10.0.19041.0 • Upgraded to latest Visual Studio 2022 Builds

Product Compatible and additional computed target framework versions.
.NET Framework net40 is compatible.  net403 was computed.  net45 was computed.  net451 was computed.  net452 was computed.  net46 was computed.  net461 was computed.  net462 was computed.  net463 was computed.  net47 was computed.  net471 was computed.  net472 was computed.  net48 was computed.  net481 was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

This package has no dependencies.

NuGet packages (1)

Showing the top 1 NuGet packages that depend on CudaControl:

Package Downloads
MyCaffe

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 Temporal Fusion Transformers, GPT, Seq2Seq/Attention, Single-Shot MultiBox, TripletNet, SiameseNet, NoisyNet, Deep Q-Network and Policy Gradient Reinforcement Learning, cuDNN LSTM Recurrent Learning, and Neural Style Transfer support!

GitHub repositories (1)

Showing the top 1 popular GitHub repositories that depend on CudaControl:

Repository Stars
MyCaffe/MyCaffe
A complete deep learning platform written almost entirely in C# for Windows developers! Now you can write your own layers in C#!
Version Downloads Last Updated
1.12.2.41 473 9/18/2023
1.12.1.82 327 6/8/2023
1.12.0.60 511 2/21/2023
1.11.8.27 606 11/23/2022
1.11.7.7 824 8/8/2022
1.11.6.38 872 6/10/2022
0.11.6.86-beta1 302 2/11/2022
0.11.4.60-beta1 376 9/11/2021
0.11.3.25-beta1 336 5/19/2021
0.11.2.9-beta1 390 2/3/2021
0.11.1.132-beta1 399 11/21/2020
0.11.1.56-beta1 424 10/17/2020
0.11.0.188-beta1 469 9/24/2020
0.11.0.65-beta1 528 8/6/2020
0.10.2.309-beta1 612 5/31/2020
0.10.2.124-beta1 536 1/21/2020
0.10.2.38-beta1 488 11/29/2019
0.10.1.283-beta1 481 10/28/2019
0.10.1.221-beta1 543 9/17/2019
0.10.1.169-beta1 563 7/8/2019
0.10.1.145-beta1 569 5/31/2019
0.10.1.48-beta1 577 4/18/2019
0.10.1.21-beta1 567 3/5/2019
0.10.0.190-beta1 717 1/15/2019
0.10.0.140-beta1 708 11/29/2018
0.10.0.122-beta1 688 11/15/2018
0.10.0.75-beta1 808 10/7/2018

The CudaControl is used by the MyCaffe AI Platform for efficient access to CUDA and cuDNN.