Fastor
Google Test
Fastor | Google Test | |
---|---|---|
5 | 67 | |
706 | 33,117 | |
- | 1.7% | |
4.3 | 8.3 | |
22 days ago | 3 days ago | |
C++ | C++ | |
MIT License | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Fastor
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Standard way of doing maths with arrays?
I'm going to throw in a recommendation for Fastor. It is generally faster than other libraries, is very lightweight, and has a pretty modern syntax.
- LibRapid -- High Performance Arrays for C++
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From Julia to C++ Struggle
There are C++ libraries that deal with linear algebra and tensors that are able to produce fully vectorized code without requiring you to mess around with SIMD intrinsics. See, for instance, fastor, blaze, eigen and the huge Trillinos set of packages. C++ is very widely used when it comes to scientific HPC applications. All you need to do is google search or better yet, join r/cpp and r/cpp_questions and start asking away for the things you need. The C++ community is very welcoming and full of experts that will be able to help you.
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Use of BLAS vs direct SIMD for linear algebra library operations?
Picking what size you are targeting is really important, though. Could the matrices you are working with realistically be bigger than say 32x32? BLAS is good for big matrices. It's not as great for small matrices. Eigen or Fastor will do better for these smaller problems. And for various common operations on sizes 2, 3, and 4, hand coded graphics-oriented libraries might outperform those.
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Scientific computing in Cpp
Tensorflow, Machine learning: https://www.tensorflow.org/ Fastor, A tensor library: https://github.com/romeric/Fastor GNU Scientific Library(GSL): https://www.gnu.org/software/gsl/ Boost. FEniCS, A finite element library: https://fenicsproject.org/ Intel MKL, a BLAS+LAPACK+other goodies library: https://software.intel.com/content/www/us/en/develop/tools/math-kernel-library.html SuiteSparse, A sparse linear algebra library: http://faculty.cse.tamu.edu/davis/suitesparse.html Sundials, Nonlinear solvers: https://computing.llnl.gov/projects/sundials
Google Test
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Creating k-NN with C++ (from Scratch)
cmake_minimum_required(VERSION 3.5) project(knn_cpp CXX) include(FetchContent) FetchContent_Declare( googletest GIT_REPOSITORY https://github.com/google/googletest.git GIT_TAG release-1.11.0 ) FetchContent_MakeAvailable(googletest) FetchContent_Declare(matplotplusplus GIT_REPOSITORY https://github.com/alandefreitas/matplotplusplus GIT_TAG origin/master) FetchContent_GetProperties(matplotplusplus) if(NOT matplotplusplus_POPULATED) FetchContent_Populate(matplotplusplus) add_subdirectory(${matplotplusplus_SOURCE_DIR} ${matplotplusplus_BINARY_DIR} EXCLUDE_FROM_ALL) endif() function(knn_cpp_test TEST_NAME TEST_SOURCE) add_executable(${TEST_NAME} ${TEST_SOURCE}) target_link_libraries(${TEST_NAME} PUBLIC matplot) aux_source_directory(${CMAKE_CURRENT_SOURCE_DIR}/../lib LIB_SOURCES) target_link_libraries(${TEST_NAME} PRIVATE gtest gtest_main gmock gmock_main) target_include_directories(${TEST_NAME} PRIVATE ${CMAKE_CURRENT_SOURCE_DIR} ${CMAKE_CURRENT_SOURCE_DIR}/../) target_sources(${TEST_NAME} PRIVATE ${LIB_SOURCES} ) include(GoogleTest) gtest_discover_tests(${TEST_NAME}) endfunction() knn_cpp_test(LinearAlgebraTest la_test.cc) knn_cpp_test(KnnTest knn_test.cc) knn_cpp_test(UtilsTest utils_test.cc)
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Starting with C
Okay, time to start unit tests!!! We will use Unity Test Framework to do unit testing. It is one of widely used testing frameworks alongside with Check, Google Test etc. Just downloading source code, and putting it to the project folder is enough to make it work (that is also why it is portable).
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Just in case: Debian Bookworm comes with a buggy GCC
Updating GCC (it happened to GoogleTest).
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Automatically run tests, formatters & linters with CI!
Roy's project uses Google Test, a C++ testing framework. His testing setup is similar to mine as we both keep source files in one directory and tests in another. The key difference is that I can run the tests using the Visual Studios run button. It was fairly easy to write the new tests as there were existing ones that I could reference to check the syntax!
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C++ Unit Testing Using Google Test - My Experience
The Google Test Documentation provides a primer for first-time users. The primer introduces some basic concepts and terminology, some of which I've been able to learn for this lab exercise.
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Basic C++ Unit Testing with GTest, CMake, and Submodules
> git submodule add https://github.com/google/googletest.git > git submodule update --init --recursive
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VS code + cmake + gtest?
cmake_minimum_required(VERSION 3.14) project(my_project) # GoogleTest requires at least C++14 set(CMAKE_CXX_STANDARD 14) set(CMAKE_CXX_STANDARD_REQUIRED ON) include(FetchContent) FetchContent_Declare( googletest URL https://github.com/google/googletest/archive/03597a01ee50ed33e9dfd640b249b4be3799d395.zip ) # For Windows: Prevent overriding the parent project's compiler/linker settings set(gtest_force_shared_crt ON CACHE BOOL "" FORCE) FetchContent_MakeAvailable(googletest) enable_testing() add_executable( hello_test hello_test.cpp ) target_link_libraries( hello_test GTest::gtest_main ) include(GoogleTest) gtest_discover_tests(hello_test)
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FetchContent with Multiple URLs
FetchContent\_Declare(googletestGIT\_REPOSITORY [[email protected]](mailto:[email protected]):googletest.git [https://github.com/google/googletest.git](https://github.com/google/googletest.git)GIT\_TAG release-1.12.1)FetchContent\_MakeAvailable(googletest)
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CI/CD pipelines for embedded
Not sure about CppUnit but I can speak to my previous experience using the googletest framework which compiles your tests to an executable, and since it's a very simple framework we were able to cross-compile and run directly on our device. We just had to hook up a device to the server that was running the CI so it could flash it when needed. That basically meant that our process was:
- Basic CMake question regarding subdirectories
What are some alternatives?
xtensor - C++ tensors with broadcasting and lazy computing
Catch - A modern, C++-native, test framework for unit-tests, TDD and BDD - using C++14, C++17 and later (C++11 support is in v2.x branch, and C++03 on the Catch1.x branch)
DirectXMath - DirectXMath is an all inline SIMD C++ linear algebra library for use in games and graphics apps
Boost.Test - The reference C++ unit testing framework (TDD, xUnit, C++03/11/14/17)
dynarray - A header-only library, VLA for C++ (≥C++14). Extended version of std::experimental::dynarray
CppUTest - CppUTest unit testing and mocking framework for C/C++
ITensors.jl - A Julia library for efficient tensor computations and tensor network calculations
CppUnit - C++ port of JUnit
sundials - Official development repository for SUNDIALS - a SUite of Nonlinear and DIfferential/ALgebraic equation Solvers. Pull requests are welcome for bug fixes and minor changes.
doctest - The fastest feature-rich C++11/14/17/20/23 single-header testing framework
ArrayFire - ArrayFire: a general purpose GPU library.
Unity Test API - Simple Unit Testing for C