Found 112 packages
Easy to use SIMD accelerated span and array methods Now each method in SimdOps is generic, instead of SimdOps<T>, i.e SimdOps.Abs<T>() instead of SimdOps<T>.Abs().
Blake3.NET is a managed wrapper around the Rust implementations of the BLAKE3 cryptographic hash function.
A .NET library for reading and writing delimited CSV data.
Optimized implementations of the BLAKE2b and BLAKE2s cryptographic hashing algorithms. Uses SSE2-SSE4.1 Hardware Intrinsics support on .NET Core 2.1+ and AVX2 on .NET Core 3+
A library for base64 encoding / decoding, as well as base64url support. For .NET Core 3.0 onwards encoding / decoding is done with SIMD-support.
Drop-in replacement of LINQ aggregation operations extremely faster with SIMD.
Provides SIMD-accelerated operations (create, init, map, ...) on native arrays provided by the NativeInterop package Note for F# Users: The System.Numerics.Vectors package doesn't work out of the box for F# projects. Make sure to MANUALLY ADD <HintPath>..\packages\System.Numerics.Vectors.4.1.1\lib\net46\System.Numerics.Vectors.dll</HintPath> to the reference in your fsproj file!
High performance Linq-style extension methods that use System.Numerics SIMD for arrays.
SimdJson: Parsing gigabytes of JSON per second. C# version of Daniel Lemire's SimdJson (written in C).
This package gives Xamarin support for Swift4. Includes libswiftsimd.dylib
SimdJson.Bindings: Parsing gigabytes of JSON per second. C# bindings for lemire/simdjson (written in C++).
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, matrix inverse, etc.) - reduction operations (sum, product, average, maximum, arg max, etc.) - logic operations (comparision, and, or, etc.) - views, slicing, reshaping, broadcasting (similar to NumPy) - scatter and gather by indices - standard functional operations (map, fold, etc.) Data exchange: - read/write support for HDF5 (.h5) - interop with standard F# types (Seq, List, Array, Array2D, Array3D, etc.) Performance: - host: SIMD and BLAS accelerated operations - by default Intel MKL is used (shipped with NuGet package) - other BLASes (OpenBLAS, vendor-specific) can be selected by configuration option - CUDA GPU: all operations performed locally on GPU and cuBLAS used for matrix operations Requirements: - Linux, MacOS or Windows on x64 - Linux requires libgomp.so.1 installed. Additional algorithms are provided in the Tensor.Algorithm package.
High performance Linq-style extension methods that are multithreaded and use System.Numerics SIMD for arrays and lists.
This package gives Xamarin support for Swift3. Includes libswiftsimd.dylib
Incredibly fast hashmap
High performance packages used by X86-SIMD
ALGLIB is a cross-platform numerical analysis and data processing library
This library contains SIMD-accelerated routines for sorting int or float arrays. The sorting algorithm implements a periodic sorting network. The code uses AVX2 instructions and runs only on x64 architecture. Introductory and API documentation is available at https://zvrba.github.io/Podaga/html/e165bf08-271a-48ee-a361-c437960f8c68.htm
Low-level fast SIMD algorithms in C#. Cross-platform, trimmable and AOT/NativeAOT compatible.
A collection of AVX2 and AVX512 accelerated mathematical functions for .NET