Scientific Computing

GitHub Actions environment variables have distinct scopes:

• Workflow
• Job
• Step

It’s trivial to set static environment variables in each of these scopes. Dynamically setting environment variables is also possible.

Workflow

Set static workflow environment variables in GitHub Actions by using env: at the top level of a “.github/workflows/ci.yml” file like:

name: ci

env:
  CTEST_PARALLEL_LEVEL: 0
  CMAKE_BUILD_PARALLEL_LEVEL: 4
  CTEST_NO_TESTS_ACTION: error
  CMAKE_GENERATOR: Ninja
  CC: gcc

Job

Static job environment variables are set like:

jobs:

  base:
    runs-on: macos-latest

    strategy:
      matrix:
        cc: [gcc-13, clang]

    env:
      CMAKE_GENERATOR: Ninja
      CC: ${{ matrix.cc }}

Step

Set static step environment variables like:

    - run: cmake -B build
      env:
        CMAKE_GENERATOR: Ninja

Clang, LLVM Flang Fortran compiler, GCC, Boost and many more packages are easily available on Windows via MSYS2. Clang is also available via direct download.

it’s often useful to have separate development environments for each compiler. The Powershell script “clang.ps1” creates a Clang LLVM environment. We don’t permanently put Clang on the user or system PATH to avoid DLL conflicts. Running “clang.ps1” in Powershell enables Clang until that Powershell window is closed.

For MSYS2 Clang and LLVM Flang Fortran compiler, create “clang.ps1” like:

$r="$Env:SystemDrive/msys64/ucrt64"
$b="$r/bin"

$Env:CC="$b/clang"
$Env:CXX="$b/clang++"
$Env:FC="$b/flang"

# important to put UCRT first to avoid "collect2.exe: error: ld returned 116 exit status" and DLL Hell
$Env:Path = "$b;$Env:Path"

$Env:CMAKE_PREFIX_PATH="$r"

For standalone (non-MSYS2) Clang make “clang.ps1” like:

$Env:CC="clang"
$Env:CXX="clang++"
$Env:Path = "$Env:ProgramFiles/LLVM/bin;$Env:Path"

If you need to use the MSVC CL-like clang driver clang-cl, create “clang-cl.ps1” and run it when desired.

$Env:CC="clang-cl"
$Env:CXX="clang-cl"
$Env:Path = "$Env:ProgramFiles/LLVM/bin;$Env:Path"

HDF4 is a predecessor to the industry-standard HDF5 data file format. This HDF4 CMake example shows how to build and link HDF4 seamlessly with Fortran example code.

Users and developers might accidentally build a program or library without optimizations when they are desired. This could make the runtime 10 to 1000 times or more slower than it would be with optimizations. This could be devastating in computational cost on HPC and cause needless schedule delays. Programmatically detecting or using a heuristic to determine if a program was built with optimizations can help prevent this. Such methods are language-specific.

• CMake, NDEBUG is set if CMAKE_BUILD_TYPE is Release or RelWithDebInfo.
• Meson: NDEBUG is set if buildtype is release or debugoptimized with

project(..., default_options: ['b_ndebug=if-release'])

C / C++

There is currently no universal language standard method in C / C++ to determine if optimization was used on build. The presence of macro NDEBUG is used by the standard library to disable assertions. One could use if NDEBUG is defined as an indication if optimizations were used.

bool fs_is_optimized(){
// This is a heuristic, trusting the build system or user to set NDEBUG if optimized.
#if defined(NDEBUG)
  return true;
#else
  return false;
#endif
}

Fortran

If the Fortran code is compiled with preprocessing, a method using NDEBUG as above could be used. Fortran iso_fortran_env provides functions compiler_version and compiler_options. These could be used in a fine-grained, per compiler way to determine if optimizations were used.

Python

Distributed Python environments would virtually always be optimized. One can use heuristic checks to help indicate if the Python executable was built in debug mode. I am not yet aware of a universal method to determine if the CPython executable was built with optimizations.

import sysconfig

debug = bool(sysconfig.get_config_var('Py_DEBUG'))

HDF5 command line tools h5dump and h5ls are handy to quickly explore HDF5 files from the command line. Backup link to old documentation. They are particularly useful when accessing a remote computer such as HPC where the HDF5 files may be very large and would take a while to transfer to a local computer.

h5ls provides a high-level look at objects in an HDF5 file. Typically we start examining HDF5 files by printing the dataset hierarchy:

h5ls --recursive my.h5

Determine the filters used (e.g. was the data compressed):

h5ls --verbose my.h5

h5dump can print the entire contents of an HDF5 file to the screen. This can be overwhelming, so we typically print only the headers to start:

h5dump --header my.h5

Individual variables can be printed like:

h5dump --dataset=myvar my.h5

Determine the filters used (e.g. was the data compressed):

h5dump --properties --header --dataset=myvar my.h5

Related: HDF5 data GUI

The C++ Standard Library uses size_type as a property of containers like std::vector, std::string, etc. This is generally recommended over using size_t directly.

Example C++ code snippets using size_type property:

std::vector<int> vec;

std::vector<int>::size_type L = vec.size();

//----------------------------------------------
std::string path = "/usr/bin:/usr/local/bin";
constexpr char pathsep = ':';

std::string::size_type start = 0;
std::string::size_type end = path.find_first_of(pathsep, start);

Related: ssize_t for Visual Studio

Intel oneAPI is a cross-platform toolset that covers several programming languages including C, C++, Fortran and Python. Intel oneAPI replaces Intel Parallel Studio. Intel oneAPI including the C++ “icpx” compiler, Fortran “ifx” compiler, and Intel MPI is free-to-use and no login is required to download oneAPI.

We suggest using the “online installer” download, which is a small download. The “online” installer can be copied over SSH to an HPC user directory for example and installed from the Terminal.

Windows requires Visual Studio Community to be installed first–IDE integration is optional and we don’t use it. Visual Studio integration is optional–if installed, cmake -G "Visual Studio 17 2022" can be used to generate Visual Studio project files.

Install the oneAPI Base Toolkit with options:

• Math Kernel Library (oneMKL)
• (optional) GDB debugger

Install oneAPI HPC toolkit with options:

• Intel MPI library
• Intel C++ compiler
• Intel Fortran compiler

Usage

There are distinct usage patterns to access Intel oneAPI compilers on Windows vs. Linux. Set environment variables CC, CXX, FC via script. oneapi-vars sets environment variable CMAKE_PREFIX_PATH so don’t just blindly overwrite that environment variable.

Windows

On Windows a Start menu shortcut for a oneAPI command prompt is installed. Powershell can also use “oneapi-vars.bat” to set the environment variables as per the oneapi.ps1 in the Gist above.

If CMake Visual Studio generater is desired, ensure:

• CMake ≥ 3.29 is used
• Intel oneAPI Visual Studio integrations are installed
• use CMake configure options

cmake -Bbuild -G "Visual Studio 17 2022" -T fortran=ifx

Troubleshooting:

If problems with finding packages with oneAPI on Windows and CMake occur, ensure that MSYS2 paths aren’t mixed in with the oneAPI environment. See the project CMakeConfigureLog.yaml and look for unwanted paths in the include commands.

Linux

On Linux, oneAPI requires GNU GCC toolchain. Some HPC systems have a too-old GCC version default for Intel oneAPI. This can cause problems with C++ STL linking. If needed, set environment variable CXXFLAGS for Intel GCC toolchain in custom “oneapi.sh” like:

export CXXFLAGS=--gcc-toolchain=/opt/rh/gcc-toolset-12/root/usr/

which can be determined like:

scl enable gcc-toolset-12 "which g++"

If using a CMake toolchain file, instead of CXXFLAGS environment variable, one can set

set(CMAKE_CXX_COMPILER_EXTERNAL_TOOLCHAIN "/opt/rh/gcc-toolset-12/root/usr/")

CI runners across CI services often update software images regularly, perhaps weekly. This can break workflows, but reflects user devices.

GitHub Actions updates the runners weekly or so. A few times a year on average across projects and operating system this may require updating the CI YaML configuration. Apple updates of XCode a few times a year this can disrupt end users and CI runs.

To have a version stable CI image would generally require private on-premises CI like Jenkins or GitHub Actions for on-premises. Those on-premises CI runners then need maintenance.

The key issue with such frozen CI runners is they are out of date with what end users have. For example, macOS with Homebrew is probably the majority of scientific computing users besides HPC. Homebrew updates often and breaks occur across projects a few times a year. Better to catch that in CI rather than on end user devices.

CMake can detect if a project is “top level” that is, NOT via FetchContent using PROJECT_IS_TOP_LEVEL and PROJECT_NAME_IS_TOP_LEVEL . For simplicity, we denote these variables in this article as “*_IS_TOP_LEVEL”.

Example use:

if(${PROJECT_NAME}_IS_TOP_LEVEL)
  message(STATUS "${PROJECT_NAME} directly building, not FetchContent")
endif()

For CMake < 3.21:

if(CMAKE_VERSION VERSION_LESS 3.21)
  get_property(not_top DIRECTORY PROPERTY PARENT_DIRECTORY)
  if(not_top)
    set(${PROJECT_NAME}_IS_TOP_LEVEL false)
  else()
    set(${PROJECT_NAME}_IS_TOP_LEVEL true)
  endif()
endif()

Caveats

Directory property PARENT_DIRECTORY and *_IS_TOP_LEVEL are NOT useful for detecting if the child project is being used as an ExternalProject.

These variables are based on the last “project()” command and so are not as universally useful as it first seems. For example, these variables do not work as expected when using ExternalProject. Even setting CMAKE_CACHE_ARGS of ExternalProject does not help, nor does cmake (1) command line options–the CMake-internal setting of *_IS_TOP_LEVEL overrides this attempt to set it. To workaround this, use an arbitrary auxiliary variable to detect if the project is top level.

Example:

Top-level CMakeLists.txt:

ExternalProject_Add(sub1
...
CMAKE_ARGS -DSUB1_IS_TOP:BOOL=false
)

ExternalProject_Add(sub2
...
CMAKE_ARGS -DSUB2_IS_TOP:BOOL=false
)

Subproject CMakeLists.txt

if(DEFINED SUB1_IS_TOP)
  set(SUB1_IS_TOP_LEVEL ${SUB1_IS_TOP})
endif()

Rather than try to directly workaround all the corner cases of *_IS_TOP_LEVEL, using this auxiliary variable allows the user to clearly force the intended behavior. This is useful when the subprojects and main project can build required ExternalProjects, and you want to only build the required ExternalProjects once.

GCC on macOS including Homebrew-installed depends on the macOS SDK. When the macOS SDK is updated, the system headers may become incompatible with GCC versions < 13.3. Specifically, there can be syntax changes requiring C23 but that GCC < 13.3 could not handle.

Homebrew GCC 14.1 and newer work just fine, so the solution is to update GCC.