simdjson-go - Golang port of simdjson: parsing gigabytes of JSON per second

•    Go

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This is a Golang port of simdjson, a high performance JSON parser developed by Daniel Lemire and Geoff Langdale. It makes extensive use of SIMD instructions to achieve parsing performance of gigabytes of JSON per second. Performance wise, simdjson-go runs on average at about 40% to 60% of the speed of simdjson. Compared to Golang's standard package encoding/json, simdjson-go is about 10x faster.

tape json-files ndjson json-document simdjson tape-format golang-standard

Simd - C++ image processing library with using of SIMD: SSE, SSE2, SSE3, SSSE3, SSE4

•    C++

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The Simd Library is a free open source image processing library, designed for C and C++ programmers. It provides many useful high performance algorithms for image processing such as: pixel format conversion, image scaling and filtration, extraction of statistic information from images, motion detection, object detection (HAAR and LBP classifier cascades) and classification, neural network. 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 (big-endian), NEON for ARM.

simd sse avx neon image-processing altivec c-plus-plus vsx sse2 avx2 ssse3 simd-library sse41 arm powerpc lbp haar-cascade avx512

simdjson - Parsing gigabytes of JSON per second

•    C++

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JSON documents are everywhere on the Internet. Servers spend a lot of time parsing these documents. We want to accelerate the parsing of JSON per se using commonly available SIMD instructions as much as possible while doing full validation (including character encoding). A description of the design and implementation of simdjson appears at https://arxiv.org/abs/1902.08318 and an informal blog post providing some background and context is at https://branchfree.org/2019/02/25/paper-parsing-gigabytes-of-json-per-second/.

json json-parser simd

Vc - SIMD Vector Classes for C++

•    C++

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Recent generations of CPUs, and GPUs in particular, require data-parallel codes for full efficiency. Data parallelism requires that the same sequence of operations is applied to different input data. CPUs and GPUs can thus reduce the necessary hardware for instruction decoding and scheduling in favor of more arithmetic and logic units, which execute the same instructions synchronously. On CPU architectures this is implemented via SIMD registers and instructions. A single SIMD register can store N values and a single SIMD instruction can execute N operations on those values. On GPU architectures N threads run in perfect sync, fed by a single instruction decoder/scheduler. Each thread has local memory and a given index to calculate the offsets in memory for loads and stores. Current C++ compilers can do automatic transformation of scalar codes to SIMD instructions (auto-vectorization). However, the compiler must reconstruct an intrinsic property of the algorithm that was lost when the developer wrote a purely scalar implementation in C++. Consequently, C++ compilers cannot vectorize any given code to its most efficient data-parallel variant. Especially larger data-parallel loops, spanning over multiple functions or even translation units, will often not be transformed into efficient SIMD code.

vectorization parallel simd-vector simd-instructions simd avx c-plus-plus avx512 sse neon cpp portable cpp11 cpp14 cpp17 avx2 simd-programming data-parallel parallel-computing

Fit - C++ function utility library

•    C++

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Fit is a header-only C++11/C++14 library that provides utilities for functions and function objects, which can solve many problems with much simpler constructs than whats traditionally been done with metaprogramming. This requires a C++11 compiler. There are no third-party dependencies. This has been tested on clang 3.5-3.8, gcc 4.6-6.2, and Visual Studio 2015. Gcc 5.1 is not supported at all, however, gcc 5.4 is supported.

modern constexpr cplusplus lambda functional c-plus-plus cplusplus-11 cplusplus-14 cpp cpp11 cpp14 functional-programming

hof - Higher-order functions for c++

•    C++

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HigherOrderFunctions is a header-only C++11/C++14 library that provides utilities for functions and function objects, which can solve many problems with much simpler constructs than whats traditionally been done with metaprogramming. This requires a C++11 compiler. There are no third-party dependencies. This has been tested on clang 3.5-3.8, gcc 4.6-7, and Visual Studio 2015 and 2017.

modern constexpr cplusplus lambda functional c-plus-plus cplusplus-11 cplusplus-14 cpp cpp11 cpp14 functional-programming

mkl-dnn - Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN)

•    C++

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Intel MKL-DNN repository migrated to https://github.com/intel/mkl-dnn. The old address will continue to be available and will redirect to the new repo. Please update your links. Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN) is an open source performance library for deep learning applications. The library accelerates deep learning applications and framework on Intel(R) architecture. Intel(R) MKL-DNN contains vectorized and threaded building blocks which you can use to implement deep neural networks (DNN) with C and C++ interfaces.

intel mkl-dnn deep-learning deep-neural-networks cnn rnn lstm c-plus-plus intel-architecture xeon xeon-phi atom core simd sse42 avx2 avx512 avx512-vnni performance

zapcc - zapcc is a caching C++ compiler based on clang, designed to perform faster compilations

•    C++

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zapcc is a caching C++ compiler based on clang, designed to perform faster compilations. zapcc uses in-memory compilation cache in client-server architecture, remembering all compilation information between runs. zapcc is the client while zapccs is the server. Each zapcc run will reuse an existing server or if none was available will start a new one. This open source release is licensed under the LLVM Release License (University of Illinois/NCSA).

clang llvm c-plus-plus precompiled-headers

libsimdpp - Portable header-only zero-overhead C++ low level SIMD library

•    C++

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libsimdpp is a portable header-only zero-overhead C++ low level SIMD library. The library presents a single interface over SIMD instruction sets present in x86, ARM, PowerPC and MIPS architectures. On architectures that support different SIMD instruction sets the library allows the same source code files to be compiled for each SIMD instruction set and then hooked into an internal or third-party dynamic dispatch mechanism. This allows the capabilities of the processor to be queried on runtime and the most efficient implementation to be selected. The library sits somewhere in the middle between programming directly in SIMD intrinsics and even higher-level SIMD libraries. As much control as possible is given to the developer, so that it's possible to exactly predict what code the compiler will generate.

sse avx2 avx512 neon vsx msa altivec simd

ccache - ccache – a fast compiler cache

•    C

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ccache is a compiler cache. It speeds up recompilation by caching the result of previous compilations and detecting when the same compilation is being done again. Supported languages are C, C++, Objective-C and Objective-C++.

ccache compiler cache c-plus-plus gcc clang cpp cplusplus

clang - Mirror of official clang git repository located at http://llvm

•    C++

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Mirror of official clang git repository located at http://llvm.org/git/clang. Updated every five minutes.

compiler c-plus-plus performance coding-style static-analyzer

libfacedetection - An open source library for face detection in images

•    C++

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This is an open source library for CNN-based face detection in images. The CNN model has been converted to static variables in C source files. 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.

face-detection cnn arm

json - JSON for Modern C++

•    C++

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Intuitive syntax. In languages such as Python, JSON feels like a first class data type. We used all the operator magic of modern C++ to achieve the same feeling in your code. Check out the examples below and you'll know what I mean.Trivial integration. Our whole code consists of a single header file json.hpp. That's it. No library, no subproject, no dependencies, no complex build system. The class is written in vanilla C++11. All in all, everything should require no adjustment of your compiler flags or project settings.

json json-pointer json-patch cbor msgpack header-only stl-containers json-serialization json-parser rfc-6901 rfc-6902 rfc-7159 rfc-7049 json-diff messagepack rfc-8259

Celero - C++ Benchmark Authoring Library/Framework

•    C++

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Developing consistent and meaningful benchmark results for code is a complex task. Measurement tools exist (Intel® VTune™ Amplifier, SmartBear AQTime, Valgrind, etc.) external to applications, but they are sometimes expensive for small teams or cumbersome to utilize. This project, Celero, aims to be a small library which can be added to a C++ project and perform benchmarks on code in a way which is easy to reproduce, share, and compare among individual runs, developers, or projects. Celero uses a framework similar to that of GoogleTest to make its API easier to use and integrate into a project. Make automated benchmarking as much a part of your development process as automated testing. Celero uses CMake to provide cross-platform builds. It does require a modern compiler (Visual C++ 2012+, GCC 4.7+, Clang 2.9+) due to its use of C++11.

benchmark benchmark-tests measurements c-plus-plus celero microbenchmarks

xsimd - C++ wrappers for SIMD intrinsics and parallelized, optimized mathematical functions (SSE, AVX, NEON, AVX512)

•    C++

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SIMD (Single Instruction, Multiple Data) is a feature of microprocessors that has been available for many years. SIMD instructions perform a single operation on a batch of values at once, and thus provide a way to significantly accelerate code execution. However, these instructions differ between microprocessor vendors and compilers. xsimd provides a unified means for using these features for library authors. Namely, it enables manipulation of batches of numbers with the same arithmetic operators as for single values. It also provides accelerated implementation of common mathematical functions operating on batches.

cpp neon c-plus-plus-11 avx sse simd vectorization avx512 mathematical-functions simd-instructions simd-intrinsics

ChaiScript - Embedded Scripting Language Designed for C++

•    C++

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Release under the BSD license, see "license.txt" for details. ChaiScript requires a C++14 compiler to build with support for variadic templates. It has been tested with gcc 4.9 and clang 3.6 (with libcxx). For more information see the build dashboard.

c-plus-plus embedded-scripting-language cpp language

Sophus - C++ implementation of Lie Groups using Eigen.

•    C++

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This is a c++ implementation of Lie groups commonly used for 2d and 3d geometric problems (i.e. for Computer Vision or Robotics applications). Among others, this package includes the special orthogonal groups SO(2) and SO(3) to present rotations in 2d and 3d as well as the special Euclidean group SE(2) and SE(3) to represent rigid body transformations (i.e. rotations and translations) in 2d and 3d. Sophus compiles with clang and gcc on Linux and OS X as well as msvc on Windows. The specific compiler and operating system versions which are supported are the ones which are used in the Continuous Integration (CI): See TravisCI and AppVeyor for details.

c-plus-plus math robotics computer-vision geometry graphics 3d 2d

pikkr - JSON parser which picks up values directly without performing tokenization in Rust

•    Rust

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Pikkr is a JSON parser which picks up values directly without performing tokenization in Rust. This JSON parser is implemented based on Y. Li, N. R. Katsipoulakis, B. Chandramouli, J. Goldstein, and D. Kossmann. Mison: a fast JSON parser for data analytics. In VLDB, 2017. This JSON parser performs well when there are a limited number of different JSON structural variants in a JSON data stream or JSON collection, and that is a common case in data analytics field.

pikkr json json-parser simd

xsimd - Modern, portable C++ wrappers for SIMD intrinsics and parallelized, optimized math implementations

•    C++

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SIMD (Single Instruction, Multiple Data) is a feature of microprocessors that has been available for many years. SIMD instructions perform a single operation on a batch of values at once, and thus provide a way to significantly accelerate code execution. However, these instructions differ between microprocessor vendors and compilers. xsimd provides a unified means for using these features for library authors. Namely, it enables manipulation of batches of numbers with the same arithmetic operators as for single values. It also provides accelerated implementation of common mathematical functions operating on batches.

simd-intrinsics c-plus-plus-14 vectorization simd cpp avx neon sse avx512 simd-instructions mathematical-functions

ComputeLibrary - The ARM Computer Vision and Machine Learning library is a set of functions optimised for both ARM CPUs and GPUs using SIMD technologies

•    C++

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License & Contributions: The software is provided under MIT license. Contributions to this project are accepted under the same license.

neon opencl computer-vision arm armv7 armv8 aarch64 machine-learning simd android cpp neural-network