SimpleSIMD 1.7.0

Suggested Alternatives

SimpleSIMD 1.8.0

Additional Details

Major conversion bug for byte, sbyte, short, ushort in MathOps

There is a newer version of this package available.
See the version list below for details.
dotnet add package SimpleSIMD --version 1.7.0
NuGet\Install-Package SimpleSIMD -Version 1.7.0
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="SimpleSIMD" Version="1.7.0" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add SimpleSIMD --version 1.7.0
#r "nuget: SimpleSIMD, 1.7.0"
#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.
// Install SimpleSIMD as a Cake Addin
#addin nuget:?package=SimpleSIMD&version=1.7.0

// Install SimpleSIMD as a Cake Tool
#tool nuget:?package=SimpleSIMD&version=1.7.0

Easy to use SIMD accelerated array extensions

Product Compatible and additional computed target framework versions.
.NET net5.0 was computed.  net5.0-windows was computed.  net6.0 was computed.  net6.0-android was computed.  net6.0-ios was computed.  net6.0-maccatalyst was computed.  net6.0-macos was computed.  net6.0-tvos was computed.  net6.0-windows was computed.  net7.0 was computed.  net7.0-android was computed.  net7.0-ios was computed.  net7.0-maccatalyst was computed.  net7.0-macos was computed.  net7.0-tvos was computed.  net7.0-windows was computed.  net8.0 was computed.  net8.0-android was computed.  net8.0-browser was computed.  net8.0-ios was computed.  net8.0-maccatalyst was computed.  net8.0-macos was computed.  net8.0-tvos was computed.  net8.0-windows was computed. 
.NET Core netcoreapp3.1 is compatible. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.
  • .NETCoreApp 3.1

    • No dependencies.

NuGet packages (3)

Showing the top 3 NuGet packages that depend on SimpleSIMD:

Package Downloads
FaceAiSharp.Bundle

FaceAiSharp allows you to work with face-related computer vision tasks easily. It currently provides face detection, face recognition, facial landmarks detection, and eye state detection functionalities. FaceAiSharp leverages publicly available pretrained ONNX models to deliver accurate and efficient results and offers a convenient way to integrate them into your .NET applications. Whether you need to find faces, recognize individuals, detect facial landmarks, or determine eye states, FaceAiSharp simplifies the process with its simple API. ONNXRuntime is used for model inference, enabling hardware acceleration were possible. All processing is done locally, with no reliance on cloud services. This is a bundle package that installs FaceAiSharp's managed code and multiple AI models in the ONNX format.

FaceAiSharp

FaceAiSharp allows you to work with face-related computer vision tasks easily. It currently provides face detection, face recognition, facial landmarks detection, and eye state detection functionalities. FaceAiSharp leverages publicly available pretrained ONNX models to deliver accurate and efficient results and offers a convenient way to integrate them into your .NET applications. Whether you need to find faces, recognize individuals, detect facial landmarks, or determine eye states, FaceAiSharp simplifies the process with its simple API. ONNXRuntime is used for model inference, enabling hardware acceleration were possible. All processing is done locally, with no reliance on cloud services. This package contains just FaceAiSharp's managed code and does not include any ONNX models. Take a look at FaceAiSharp.Bundle for a batteries-included package with everything you need to get started.

STensor

SIMD-accelerated generic tensor library

GitHub repositories

This package is not used by any popular GitHub repositories.

Version Downloads Last updated
4.6.0 642 11/20/2022
4.2.0-alpha 159 8/17/2021
3.3.1 2,617 6/6/2022
3.3.0 765 8/31/2021
3.1.0 377 4/20/2021
2.5.1 344 1/25/2021
2.4.3 421 10/6/2020
2.4.2 367 10/6/2020
2.4.1-beta 263 10/6/2020
2.4.0-beta 259 10/6/2020
2.3.1 406 10/4/2020
2.3.0 371 9/28/2020
2.2.0 372 9/24/2020
2.1.1 390 9/21/2020
2.0.1 387 9/18/2020
2.0.0 423 9/17/2020
1.9.0 354 9/17/2020
1.8.0 429 9/16/2020
1.7.0 682 9/13/2020
1.6.5 525 9/12/2020
1.6.3 847 9/8/2020
1.6.2 558 9/7/2020
1.5.0 674 9/5/2020
1.2.0 557 9/5/2020
1.1.0 555 9/3/2020
1.0.0 565 9/1/2020