Search Results for "simd"
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Showing 32 open source projects for "simd"
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SIMD
C++ wrappers for SIMD intrinsics
SIMD is a C++ library that provides portable abstractions over SIMD (Single Instruction, Multiple Data) instructions, enabling developers to write high-performance vectorized code without dealing directly with architecture-specific intrinsics. SIMD instructions allow a single operation to be applied to multiple data elements simultaneously, significantly accelerating numerical and data-parallel computations. -
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HLSL++
Math library using HLSL syntax with multiplatform SIMD support
...It provides vector, matrix, and math operations with a syntax identical or very similar to HLSL, allowing seamless transition between shader code and application code. The library is optimized for performance and supports SIMD instructions across multiple architectures, including SSE, AVX, AVX2, AVX512, and ARM NEON, ensuring high efficiency on modern hardware. It also extends beyond standard HLSL capabilities by introducing additional features such as quaternion support, advanced matrix operations, and extended vector types like float8. The library is particularly valuable for game developers who need consistency between CPU and GPU computations, reducing errors and improving maintainability. -
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Google Highway
Performance-portable, length-agnostic SIMD with runtime dispatch
Google Highway is a high-performance C++ library designed to provide portable SIMD (Single Instruction, Multiple Data) vectorization across multiple CPU architectures while maintaining predictable and efficient behavior. It abstracts low-level vector intrinsics into a consistent API that maps closely to hardware instructions, allowing developers to write high-performance code without relying heavily on compiler auto-vectorization. -
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LoopVectorization.jl
Macro(s) for vectorizing loops
LoopVectorization.jl is a Julia package for accelerating numerical loops by automatically applying SIMD (Single Instruction, Multiple Data) vectorization and other low-level optimizations. It analyzes loops and generates highly efficient code that leverages CPU vector instructions, making it ideal for performance-critical computing in fields such as scientific computing, signal processing, and machine learning. -
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ispc
Intel SPMD Program Compiler
...Under the SPMD model, the programmer writes a program that generally appears to be a regular serial program, though the execution model is actually that a number of program instances execute in parallel on the hardware. ispc compiles a C-based SPMD programming language to run on the SIMD units of CPUs and GPUs; it frequently provides a 3x or more speedup on architectures with 4-wide vector SSE units and 5x-6x on architectures with 8-wide AVX vector units, without any of the difficulty of writing intrinsics code. Parallelization across multiple cores is also supported by ispc, making it possible to write programs that achieve performance improvement that scales by both numbers of cores and vector unit size. ... -
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node-rs
Node.js bindings Rust crates
When Node.js meets Rust. Make rust crates binding to Node.js use napi-rs. -
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torchvision
Datasets, transforms and models specific to Computer Vision
The torchvision package consists of popular datasets, model architectures, and common image transformations for computer vision. We recommend Anaconda as Python package management system. Torchvision currently supports Pillow (default), Pillow-SIMD, which is a much faster drop-in replacement for Pillow with SIMD, if installed will be used as the default. Also, accimage, if installed can be activated by calling torchvision.set_image_backend('accimage'), libpng, which can be installed via conda conda install libpng or any of the package managers for debian-based and RHEL-based Linux distributions, and libjpeg, which can be installed via conda conda install jpeg or any of the package managers for debian-based and RHEL-based Linux distributions. ... -
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Polars
Dataframes powered by a multithreaded, vectorized query engine
Polars is a high-performance, multi-language DataFrame library built in Rust using Apache Arrow. It delivers blazing-fast, vectorized, and parallel data manipulation with both eager and lazy execution, making it an excellent tool for data processing in Python, Rust, Node.js, R, and SQL contexts. -
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Numba
NumPy aware dynamic Python compiler using LLVM
Numba is an open source JIT compiler that translates a subset of Python and NumPy code into fast machine code. Numba translates Python functions to optimized machine code at runtime using the industry-standard LLVM compiler library. Numba-compiled numerical algorithms in Python can approach the speeds of C or FORTRAN. You don't need to replace the Python interpreter, run a separate compilation step, or even have a C/C++ compiler installed. Just apply one of the Numba decorators to your... -
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XNNPACK
High-efficiency floating-point neural network inference operators
...Rather than serving as a standalone ML framework, XNNPACK provides high-performance computational primitives—such as convolutions, pooling, activation functions, and arithmetic operations—that are integrated into higher-level frameworks like TensorFlow Lite, PyTorch Mobile, ONNX Runtime, TensorFlow.js, and MediaPipe. The library is written in C/C++ and designed for maximum portability, efficiency, and performance, leveraging platform-specific instruction sets (e.g., NEON, AVX, SIMD) for optimized execution. It supports NHWC tensor layouts and allows flexible striding along the channel dimension to efficiently handle channel-split and concatenation operations without additional cost. -
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Zerocopy
Zerocopy makes zero-cost memory manipulation effortless
Zerocopy is a Rust library designed to make zero-cost memory manipulation both safe and effortless. It allows developers to reinterpret or convert raw byte sequences into structured types—and vice versa—without writing unsafe code directly. The crate provides safe abstractions for transmuting data while preserving Rust’s strict safety guarantees, removing the need for manual memory manipulation. Zerocopy introduces a suite of conversion traits such as TryFromBytes, FromBytes, IntoBytes, and... -
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UniSIMD-assembler
SIMD macro assembler unified for ARM, MIPS, PPC and x86
UniSIMD assembler is a high-level C/C++ macro assembler framework unified across ARM, MIPS, POWER and x86 architectures. It establishes a subset of both BASE and SIMD instruction sets with clearly defined common API, so that application logic can be written and maintained in one place without code replication. The assembler itself isn't a separate tool, but rather a collection of C/C++ header files, which applications need to include directly in order to use. At present, Intel SSE/SSE2/SSE4 and AVX/AVX2/AVX-512 (32/64-bit x86 ISAs), ARMv7 NEON/NEONv2, ARMv8 AArch32 and AArch64 NEON, SVE (32/64-bit ARM ISAs), MIPS 32/64-bit r5/r6 MSA and POWER 32/64-bit VMX/VSX (little/big-endian ISAs) are mostly implemented (/w horizontal reductions) although scalar improvements, wider SIMD vectors with zeroing/merging predicates in 3/4-operand instructions are planned as extensions to current 2/3-operand SPMD-driven vertical SIMD ISA. ... -
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sleef
Vectorized libm
SLEEF stands for SIMD Library for Evaluating Elementary Functions. SLEEF implements vectorized versions of all C99 math functions, that utilize SIMD instructions of modern processors to make computation more efficient. The library also includes vectorized DFT subroutines. -
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Vector Pascal is a language targeted at SIMD multi-core instruction-sets such as the AVX and SSE2 or x86-64-v3. It has a SIMD compiler which supports parallel vector operations, loop unrolling, common sub expression removal etc. It is implemented in Java.
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HighwayHash
Fast strong hash functions: SipHash/HighwayHash
HighwayHash is a fast, keyed hash function intended for scenarios where you need strong, DoS-resistant hashing without the full overhead of a general-purpose cryptographic hash. It’s designed to defeat hash-flooding attacks by mixing input with wide SIMD operations and a branch-free inner loop, so adversaries can’t cheaply craft many colliding keys. The implementation targets multiple CPU families with vectorized code paths while keeping a portable fallback, yielding high throughput across platforms. It exposes simple one-shot and streaming APIs, so you can hash short keys or long byte streams with the same function. ... -
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GNSS-SDR
An open source software-defined GNSS receiver
An open source software-defined Global Navigation Satellite Systems (GNSS) receiver written in C++ and based on the GNU Radio framework. -
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LinAsm
Collection of fast and optimized assembly libraries for x86-64 Linux
LinAsm is collection of very fast and SIMD optimized assembly written libraries for x86-64 Linux. It implements many common and widely used algorithms for array manipulations: searching, sorting, arithmetic and vector operations, unit conversions; fast mathematical and statistic functions; numbers and time converting algorithms; finite impulse response (FIR) digital filters; spectrum analysis algorithms, Fast Hartley transformation; CPU cache friendly functions and extremely fast abstract data types (ADT) such as hash tables b-trees, and much more. ... -
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Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads:... -
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libjpeg-turbo
SIMD-accelerated libjpeg-compatible JPEG codec library
libjpeg-turbo is a JPEG image codec that uses SIMD instructions (MMX, SSE2, NEON, AltiVec) to accelerate baseline JPEG compression and decompression on x86, x86-64, ARM, and PowerPC systems. On such systems, libjpeg-turbo is generally 2-6x as fast as libjpeg, all else being equal. On other types of systems, libjpeg-turbo can still outperform libjpeg by a significant amount, by virtue of its highly-optimized Huffman coding routines. -
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TurboPFor
Fastest Integer Compression
Fastest Integer Compression. ALL functions are available for AMD/Intel, 64-bit ARMv8 NEON Linux+MacOS/M1 & Power9 Altivec. 100% C (C++ headers), as simple as memcpy. OS:Linux amd64, arm64, Power9, MacOs (Amd/intel + Apple M1). -
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Klogg
Really fast log explorer based on glogg project
Klogg is an open source multi-platform GUI application to search through all kinds of text log files using regular expressions. It has started as fork of glogg project created by Nicolas Bonnefon and has evolved into a separate project with a lot of new features and improvements. -
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libfacedetection
Library for face detection in images
...The source code does not depend on any other libraries. What you need is just a C++ compiler. You can compile the source code under Windows, Linux, ARM and any platform with a C++ compiler. SIMD instructions are used to speed up the detection. You can enable AVX2 if you use Intel CPU or NEON for ARM. The model file has also been provided in directory ./models/. The file examples/detect-image.cpp and examples/detect-camera.cpp show how to use the library. The library was trained by libfacedetection.train. You can copy the files in directory src/ into your project, and compile them as the other files in your project. ... -
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Simd
High performance image processing library in C++
...The algorithms are optimized with using of different SIMD CPU extensions. In particular the library supports following CPU extensions: SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2, AVX, AVX2 and AVX-512 for x86/x64, VMX(Altivec) and VSX(Power7) for PowerPC, NEON for ARM. The Simd Library has C API and also contains useful C++ classes and functions to facilitate access to C API. The library supports dynamic and static linking, 32-bit and 64-bit Windows, Android and Linux, MSVS, G++ and Clang compilers, MSVS project and CMake build systems. -
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jpegant
Embedded JPEG encoder
...Release 1.1 source code and Windows executables are on the download page. For the latest release code look into the repository in 'release-1-0' branch. The SSE2 inplementation is present in 'simd.0' branch in the repository. -
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SWAPHI-LS: Alignment on Xeon Phi Cluster
Smith-Waterman long DNA sequence alignment on Xeon Phi clusters
The first parallel Smith-Waterman algorithm exploiting Intel Xeon Phi clusters to accelerate the alignment of long DNA sequences. This algorithm is written in C++ (with a set of SIMD intrinsic extensions), OpenMP and MPI. The performance evaluation revealed that our algorithm achieves very stable performance, and yields a performance of up to 30.1 GCUPS on a single Xeon Phi and up to 111.4 GCUPS on four Xeon Phis sharing a host.
