universal

universal

高性能自定义算术类型C++模板库

Universal C++模板库提供自定义算术类型,支持混合精度算法开发。可定制精度和动态范围,优化性能和能效。适用于嵌入式系统和深度学习等领域。仅头文件设计,可替代原生数值类型。

Universal Numbers LibraryC++数值计算混合精度算术库Github开源项目

Universal: a header-only C++ template library of custom arithmetic plug-in types

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The goal of the Universal Numbers Library is to offer alternatives to native integer and floating-point for mixed-precision algorithm development and optimization. Tailoring the arithmetic types to the application's precision and dynamic range enables a new level of application performance and energy efficiency, particularly valuable for embedded applications that need autonomy through intelligent behavior.

Deep Learning algorithms in particular provide a core application vertical where alternative formats and precisions, such as half-precision floating-point and bfloat16, yield speed-ups of two to three orders of magnitude, making rapid innovation in AI possible.

The Universal Library is a ready-to-use header-only library that provides a plug-in replacement for native types and offers a low-friction environment to explore alternatives to IEEE-754 floating-point in AI, DSP, HPC, and HFT algorithms.

The basic use pattern is as simple as:

// bring in the parameterized type of interest, in this case // a fixed-sized, arbitrary configuration classic floating-point #include <universal/number/cfloat/cfloat.hpp> // define your computational kernel parameterized by arithmitic type template<typename Real> Real MyKernel(const Real& a, const Real& b) { return a * b; // replace this with your kernel computation } constexpr double pi = 3.14159265358979323846; int main() { // if desired, create an application type alias to avoid errors using Real = sw::universal::half; // half-precision IEEE-754 floating-point Real a = sqrt(2); Real b = pi; // finally, call your kernel with your desired arithmetic type std::cout << "Result: " << MyKernel(a, b) << std::endl; }

The library contains fast implementations of special IEEE-754 formats that do not have universal hardware implementations across x86, ARM, POWER, RISC-V, and GPUs. Special formats such as quarter precision, quarter, half-precision, half, and quad precision, quad, are provided, as well as vendor-specific extensions, such as NVIDIA TensorFloat, Google's Brain Float, bfloat16, or TI DSP fixed-points, fixpnt. In addition to these often-used specializations, Universal supports static and elastic integers, decimals, fixed-points, rationals, linear floats, tapered floats, logarithmic, interval and adaptive-precision integers, rationals, and floats. There are example number system skeletons to get you started quickly if you desire to add your own.

Communication channels

  • GitHub Issue: bug reports, feature requests, etc.
  • Forum: discussion of alternatives to IEEE-754 for computational science.
  • Slack: online chats, discussions, and collaboration with other users, researchers and developers.

Citation

Please cite our work if you use Universal.

@article{omtzigt2023universal, title={Universal Numbers Library: Multi-format Variable Precision Arithmetic Library}, author={Omtzigt, E Theodore L and Quinlan, James}, journal={Journal of Open Source Software}, volume={8}, number={83}, pages={5072}, year={2023} } @inproceedings{Omtzigt:2022, title = {Universal: Reliable, Reproducible, and Energy-Efficient Numerics}, author = {E. Theodore L. Omtzigt and James Quinlan}, booktitle = {Conference on Next Generation Arithmetic}, pages = {100--116}, year = {2022}, organization = {Springer} } @article{Omtzigt2020, author = {E. Theodore L. Omtzigt and Peter Gottschling and Mark Seligman and William Zorn}, title = {{Universal Numbers Library}: design and implementation of a high-performance reproducible number systems library}, journal = {arXiv:2012.11011}, year = {2020}, }

Talks and Presentations

The following presentations describe Universal and the number systems it contained as of the time of publication.

Slides of a presentation at FPTalks'21

Presentation: Application-Driven Custom Number Systems

Slides of the presentation at CoNGA'22

Presentation: Universal: Reliable, Reproducible, and Energy-Efficient Numerics

A quick description of the structure of the number system parameterization can be found here.

Quick start

If you just want to experiment with the number system tools and test suites and don't want to bother cloning and building the source code, there is a Docker container to get started:

> docker pull stillwater/universal > docker run -it --rm stillwater/universal bash stillwater@b3e6708fd732:~/universal/build$ ls CMakeCache.txt Makefile cmake-uninstall.cmake playground universal-config-version.cmake CMakeFiles applications cmake_install.cmake tests universal-config.cmake CTestTestfile.cmake c_api education tools universal-targets.cmake

Here is a quick reference of what the command line tools have to offer.

How to build

If you do want to work with the code, the universal numbers software library is built using cmake version v3.23. Install the latest cmake. There are interactive installers for MacOS and Windows. For Linux, a portable approach downloads the shell archive and installs it at /usr/local:

> wget https://github.com/Kitware/CMake/releases/download/v3.23.1/cmake-3.23.1-Linux-x86_64.sh > sudo sh cmake-3.23.1-Linux-x86_64.sh --prefix=/usr/local --exclude-subdir

For Ubuntu, snap will install the latest cmake, and would be the preferred method:

> sudo snap install cmake --classic

The Universal Library is a pure C++ template library without any further dependencies, even for the regression test suites to enable hassle-free installation and use.

Clone the GitHub repo, and you are ready to build the different components of the Universal library.
The library contains tools for using integers, decimals, fixed-points, floats, posits, valids, and logarithmic number systems. It includes educational programs that showcase simple use cases to familiarize yourself with different number systems and application examples to highlight the use of other number systems to gain performance or numerical accuracy. Finally, each number system offers its own verification suite.

The easiest way to become familiar with all the options in the build process is to fire up the CMake GUI (or ccmake if you are on a headless server). The CMake output will summarize which options have been set.
The output will look something like this:

$ git clone https://github.com/stillwater-sc/universal $ cd universal $ mkdir build $ cd build $ cmake .. _____ _____ ____ _____ _____ ____ ____ ________ _______ ______ _ _____ |_ _||_ _||_ \|_ _||_ _||_ _| |_ _||_ __ ||_ __ \ .' ____ \ / \ |_ _| | | | | | \ | | | | \ \ / / | |_ \_| | |__) | | (___ \_| / _ \ | | | ' ' | | |\ \| | | | \ \ / / | _| _ | __ / _.____`. / ___ \ | | _ \ \__/ / _| |_\ |_ _| |_ \ ' / _| |__/ | _| | \ \_| \____) | _/ / \ \_ _| |__/ | `.__.' |_____|\____||_____| \_/ |________||____| |___|\______.'|____| |____||________| -- The C compiler identification is GNU 9.4.0 -- The CXX compiler identification is GNU 9.4.0 -- The ASM compiler identification is GNU -- Found assembler: /usr/bin/cc -- Detecting C compiler ABI info -- Detecting C compiler ABI info - done -- Check for working C compiler: /usr/bin/cc - skipped -- Detecting C compile features -- Detecting C compile features - done -- Detecting CXX compiler ABI info -- Detecting CXX compiler ABI info - done -- Check for working CXX compiler: /usr/bin/c++ - skipped -- Detecting CXX compile features -- Detecting CXX compile features - done -- No default build type specified: setting CMAKE_BUILD_TYPE=Release -- C++20 has been enabled by default -- Performing Test COMPILER_HAS_SSE3_FLAG -- Performing Test COMPILER_HAS_SSE3_FLAG - Success -- Performing Test COMPILER_HAS_AVX_FLAG -- Performing Test COMPILER_HAS_AVX_FLAG - Success -- Performing Test COMPILER_HAS_AVX2_FLAG -- Performing Test COMPILER_HAS_AVX2_FLAG - Success -- -- PROJECT_NAME = universal -- PROJECT_NAME_NOSPACES = universal -- PROJECT_SOURCE_DIR = /home/stillwater/dev/clones/universal -- PROJECT_VERSION = 3.68.1.80df9073 -- CMAKE_C_COMPILER = /usr/bin/cc -- CMAKE_CXX_COMPILER = /usr/bin/c++ -- CMAKE_CURRENT_SOURCE_DIR = /home/stillwater/dev/clones/universal -- CMAKE_CURRENT_BINARY_DIR = /home/stillwater/dev/clones/universal/build_gcc -- GIT_COMMIT_HASH = 80df9073 -- GIT_BRANCH = v3.68 -- include_install_dir = include -- include_install_dir_full = include/universal -- config_install_dir = share/universal -- include_install_dir_postfix = universal -- -- ******************* Universal Arithmetic Library Configuration Summary ******************* -- General: -- Version : 3.68.1.80df9073 -- System : Linux -- C++ Language Requirement : C++20 -- C compiler : /usr/bin/cc -- Release C flags : -O3 -DNDEBUG -Wall -Wpedantic -Wno-narrowing -Wno-deprecated -- Debug C flags : -g -Wall -Wpedantic -Wno-narrowing -Wno-deprecated -- C++ compiler : /usr/bin/c++ -- Release CXX flags : -O3 -DNDEBUG -Wall -Wpedantic -Wno-narrowing -Wno-deprecated -Wall -Wpedantic -Wno-narrowing -Wno-deprecated -- Debug CXX flags : -g -Wall -Wpedantic -Wno-narrowing -Wno-deprecated -Wall -Wpedantic -Wno-narrowing -Wno-deprecated -- Build type : Release -- -- BUILD_ALL : OFF -- BUILD_CI : OFF -- -- BUILD_DEMONSTRATION : ON -- BUILD_NUMBERS : OFF -- BUILD_NUMERICS : OFF -- BUILD_BENCHMARKS : OFF -- BUILD_MIXEDPRECISION_SDK : OFF -- -- BUILD_CMD_LINE_TOOLS : ON -- BUILD_EDUCATION : ON -- BUILD_APPLICATIONS : ON -- BUILD_PLAYGROUND : ON -- -- BUILD_NUMBER_INTERNALS : OFF -- BUILD_NUMBER_NATIVE_TYPES : OFF -- BUILD_NUMBER_ELASTICS : OFF -- BUILD_NUMBER_STATICS : OFF -- BUILD_NUMBER_CONVERSIONS : OFF -- -- BUILD_NUMBER_EINTEGERS : OFF -- BUILD_NUMBER_DECIMALS : OFF -- BUILD_NUMBER_RATIONALS : OFF -- BUILD_NUMBER_EFLOATS : OFF -- BUILD_NUMBER_EPOSITS : OFF -- -- BUILD_NUMBER_INTEGERS : OFF -- BUILD_NUMBER_FIXPNTS : OFF -- BUILD_NUMBER_BFLOATS : OFF -- BUILD_NUMBER_CFLOATS : OFF -- BUILD_NUMBER_DFLOATS : OFF -- BUILD_NUMBER_AREALS : OFF -- BUILD_NUMBER_UNUM1S : OFF -- BUILD_NUMBER_UNUM2S : OFF -- BUILD_NUMBER_POSITS : OFF -- BUILD_NUMBER_VALIDS : OFF -- BUILD_NUMBER_LNS : OFF -- BUILD_NUMBER_LNS2B : OFF -- BUILD_NUMBER_SORNS : OFF -- -- BUILD_NUMERIC_FUNCTIONS : OFF -- BUILD_NUMERIC_QUIRES : OFF -- BUILD_NUMERIC_CHALLENGES : OFF -- BUILD_NUMERIC_UTILS : OFF -- BUILD_NUMERIC_FPBENCH : OFF -- -- BUILD_BENCHMARK_ERROR : OFF -- BUILD_BENCHMARK_ACCURACY : OFF -- BUILD_BENCHMARK_REPRODUCIBILITY : OFF -- BUILD_BENCHMARK_PERFORMANCE : OFF -- BUILD_BENCHMARK_ENERGY : OFF -- -- BUILD_MIXEDPRECISION_ROOTS : OFF -- BUILD_MIXEDPRECISION_APPROXIMATE : OFF -- BUILD_MIXEDPRECISION_INTEGRATE : OFF -- BUILD_MIXEDPRECISION_INTERPOLATE : OFF -- BUILD_MIXEDPRECISION_OPTIMIZE : OFF -- BUILD_MIXEDPRECISION_TENSOR : OFF -- -- BUILD_LINEAR_ALGEBRA_BLAS : OFF -- BUILD_LINEAR_ALGEBRA_VMATH : OFF -- -- -- BUILD_C_API_PURE_LIB : OFF -- BUILD_C_API_SHIM_LIB : OFF -- BUILD_C_API_LIB_PIC : OFF --

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