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OpenBLAS/docs/install.md

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Install OpenBLAS

OpenBLAS can be installed through package managers or from source. If you only
want to use OpenBLAS rather than make changes to it, we recommend installing a
pre-built binary package with your package manager of choice.

This page contains an overview of installing with package managers as well as
from source. For the latter, see further down on this page.

Installing with a package manager

!!! note
Almost every package manager provides OpenBLAS packages; the list on this
page is not comprehensive. If your package manager of choice isn't shown
here, please search its package database for openblas or libopenblas.

Linux

On Linux, OpenBLAS can be installed with the system package manager, or with a
package manager like Conda
(or alternative package managers for the conda-forge ecosystem, like
Mamba,
Micromamba,
or Pixi),
Spack, or Nix. For the latter set of
tools, the package name in all cases is openblas. Since package management in
quite a few of these tools is declarative (i.e., managed by adding openblas
to a metadata file describing the dependencies for your project or
environment), we won't attempt to give detailed instructions for these tools here.

Linux distributions typically split OpenBLAS up in two packages: one containing
the library itself (typically named openblas or libopenblas), and one containing headers,
pkg-config and CMake files (typically named the same as the package for the
library with -dev or -devel appended; e.g., openblas-devel). Please keep
in mind that if you want to install OpenBLAS in order to use it directly in
your own project, you will need to install both of those packages.

Distro-specific installation commands:

=== "Debian/Ubuntu/Mint/Kali"

```bash
$ sudo apt update
$ sudo apt install libopenblas-dev
```
OpenBLAS can be configured as the default BLAS through the `update-alternatives` mechanism:

```bash
$ sudo update-alternatives --config libblas.so.3
```

=== "openSUSE/SLE"

```bash
$ sudo zypper refresh
$ sudo zypper install openblas-devel
```

OpenBLAS can be configured as the default BLAS through the `update-alternatives` mechanism:
```bash
$ sudo update-alternatives --config libblas.so.3
```

=== "Fedora/CentOS/RHEL"

```bash
$ dnf check-update
$ dnf install openblas-devel
```

!!! warning

    Fedora does not ship the pkg-config files for OpenBLAS. Instead, it wants you to
    link against [FlexiBLAS](https://www.mpi-magdeburg.mpg.de/projects/flexiblas) (which
    uses OpenBLAS by default as its backend on Fedora), which you can install with:

    ```bash
    $ dnf install flexiblas-devel
    ```

For CentOS and RHEL, OpenBLAS packages are provided via the [Fedora EPEL repository](https://fedoraproject.org/wiki/EPEL).
After adding that repository and its repository keys, you can install
`openblas-devel` with either `dnf` or `yum`.

=== "Arch/Manjaro/Antergos"

```bash
$ sudo pacman -S openblas
```

Windows

=== "Conda-forge"

OpenBLAS can be installed with `conda` (or `mamba`, `micromamba`, or
`pixi`) from conda-forge:
```
conda install openblas
```

Conda-forge provides a method for switching the default BLAS implementation
used by all packages. To use that for OpenBLAS, install `libblas=*=*openblas`
(see [the docs on this mechanism](https://conda-forge.org/docs/maintainer/knowledge_base/#switching-blas-implementation)
for more details).

=== "vcpkg"

OpenBLAS can be installed with vcpkg:
```cmd
# In classic mode:
vcpkg install openblas

# Or in manifest mode:
vcpkg add port openblas
```

=== "OpenBLAS releases"

Windows is the only platform for which binaries are made available by the
OpenBLAS project itself. They can be downloaded from the GitHub
Releases](https://github.com/OpenMathLib/OpenBLAS/releases) page. These
binaries are built with MinGW, using the following build options:
```
NUM_THREADS=64 TARGET=GENERIC DYNAMIC_ARCH=1 DYNAMIC_OLDER=1 CONSISTENT_FPCSR=1 INTERFACE=0
```
There are separate packages for x86-64 and x86. The zip archive contains
the include files, static and shared libraries, as well as configuration
files for getting them found via CMake or pkg-config. To use these
binaries, create a suitable folder for your OpenBLAS installation and unzip
the `.zip` bundle there (note that you will need to edit the provided
`openblas.pc` and `OpenBLASConfig.cmake` to reflect the installation path
on your computer, as distributed they have "win" or "win64" reflecting the
local paths on the system they were built on).

Note that the same binaries can be downloaded
[from SourceForge](http://sourceforge.net/projects/openblas/files); this is
mostly of historical interest.

macOS

To install OpenBLAS with a package manager on macOS, run:

=== "Homebrew"

```zsh
% brew install openblas
```

=== "MacPorts"

```zsh
% sudo port install OpenBLAS-devel
```

=== "Conda-forge"

```zsh
% conda install openblas
```

Conda-forge provides a method for switching the default BLAS implementation
used by all packages. To use that for OpenBLAS, install `libblas=*=*openblas`
(see [the docs on this mechanism](https://conda-forge.org/docs/maintainer/knowledge_base/#switching-blas-implementation)
for more details).

Building from source

We recommend download the latest stable version
from the GitHub Releases page, or checking it out from a git tag, rather than a
dev version from the develop branch.

!!! tip

The User manual contains [a section with detailed information on compiling OpenBLAS](user_manual.md#compiling-openblas),
including how to customize builds and how to cross-compile. Please read
that documentation first. This page contains only platform-specific build
information, and assumes you already understand the general build system
invocations to build OpenBLAS, with the specific build options you want to
control multi-threading and other non-platform-specific behavior).

Linux and macOS

Ensure you have C and Fortran compilers installed, then simply type make to compile the library.
There are no other build dependencies, nor unusual platform-specific
environment variables to set or other system setup to do.

!!! note

When building in an emulator (KVM, QEMU, etc.), please make sure that the combination of CPU features exposed to
the virtual environment matches that of an existing CPU to allow detection of the CPU model to succeed.
(With `qemu`, this can be done by passing `-cpu host` or a supported model name at invocation).

Windows

Visual Studio

As of OpenBLAS v0.2.15, we support MinGW and Visual Studio (using CMake to generate visual studio solution files – note that you will need at least version 3.11 of CMake for linking to work correctly) to build OpenBLAS on Windows.

Note that you need a Fortran compiler if you plan to build and use the LAPACK functions included with OpenBLAS. The sections below describe using either flang as an add-on to clang/LLVM or gfortran as part of MinGW for this purpose. If you want to use the Intel Fortran compiler ifort for this, be sure to also use the Intel C compiler icc for building the C parts, as the ABI imposed by ifort is incompatible with msvc.

1. Native (MSVC) ABI

A fully-optimized OpenBLAS that can be statically or dynamically linked to your application can currently be built for the 64-bit architecture with the LLVM compiler infrastructure. We're going to use Miniconda3 to grab all of the tools we need, since some of them are in an experimental status. Before you begin, you'll need to have Microsoft Visual Studio 2015 or newer installed.

  1. Install Miniconda3 for 64 bits using winget install --id Anaconda.Miniconda3 or easily download from conda.io.

  2. Open the "Anaconda Command Prompt," now available in the Start Menu, or at %USERPROFILE%\miniconda3\shell\condabin\conda-hook.ps1.

  3. In that command prompt window, use cd to change to the directory where you want to build OpenBLAS

  4. Now install all of the tools we need:

    conda update -n base conda
conda config --add channels conda-forge
conda install -y cmake flang clangdev perl libflang ninja

  5. Still in the Anaconda Command Prompt window, activate the MSVC environment for 64 bits with vcvarsall x64. On Windows 11 with Visual Studio 2022, this would be done by invoking:

    "c:\Program Files\Microsoft Visual Studio\2022\Preview\vc\Auxiliary\Build\vcvars64.bat"

    With VS2019, the command should be the same – except for the year number, obviously. For other/older versions of MSVC,
    the VS documentation or a quick search on the web should turn up the exact wording you need.

    Confirm that the environment is active by typing link – this should return a long list of possible options for the link command. If it just
    returns "command not found" or similar, review and retype the call to vcvars64.bat.
    NOTE: if you are working from a Visual Studio Command prompt window instead (so that you do not have to do the vcvars call), you need to invoke
    conda activate so that CONDA_PREFIX etc. get set up correctly before proceeding to step 6. Failing to do so will lead to link errors like
    libflangmain.lib not getting found later in the build.

  6. Now configure the project with CMake. Starting in the project directory, execute the following:

    set "LIB=%CONDA_PREFIX%\Library\lib;%LIB%"
set "CPATH=%CONDA_PREFIX%\Library\include;%CPATH%"
mkdir build
cd build
cmake .. -G "Ninja" -DCMAKE_CXX_COMPILER=clang-cl -DCMAKE_C_COMPILER=clang-cl -DCMAKE_Fortran_COMPILER=flang -DCMAKE_MT=mt -DBUILD_WITHOUT_LAPACK=no -DNOFORTRAN=0 -DDYNAMIC_ARCH=ON -DCMAKE_BUILD_TYPE=Release

    You may want to add further options in the cmake command here – for instance, the default only produces a static .lib version of the library. If you would rather have a DLL, add -DBUILD_SHARED_LIBS=ON above. Note that this step only creates some command files and directories, the actual build happens next.

  7. Build the project:

    cmake --build . --config Release

    This step will create the OpenBLAS library in the "lib" directory, and various build-time tests in the test, ctest and openblas_utest directories. However it will not separate the header files you might need for building your own programs from those used internally. To put all relevant files in a more convenient arrangement, run the next step.

  8. Install all relevant files created by the build

    cmake --install . --prefix c:\opt -v

    This will copy all files that are needed for building and running your own programs with OpenBLAS to the given location, creating appropriate subdirectories for the individual kinds of files. In the case of "C:\opt" as given above, this would be C:\opt\include\openblas for the header files,
    C:\opt\bin for the libopenblas.dll and C:\opt\lib for the static library. C:\opt\share holds various support files that enable other cmake-based build scripts to find OpenBLAS automatically.

Visual studio 2017+ (C++2017 standard)

In newer visual studio versions, Microsoft has changed how it handles complex types. Even when using a precompiled version of OpenBLAS, you might need to define LAPACK_COMPLEX_CUSTOM in order to define complex types properly for MSVC. For example, some variant of the following might help:

#if defined(_MSC_VER)
    #include <complex.h>
    #define LAPACK_COMPLEX_CUSTOM
    #define lapack_complex_float _Fcomplex
    #define lapack_complex_double _Dcomplex
#endif

For reference, see https://github.com/OpenMathLib/OpenBLAS/issues/3661, https://github.com/Reference-LAPACK/lapack/issues/683, and https://stackoverflow.com/questions/47520244/using-openblas-lapacke-in-visual-studio.

CMake and Visual Studio

To build OpenBLAS for the 32-bit architecture, you'll need to use the builtin Visual Studio compilers.

!!! note
This method may produce binaries which demonstrate significantly lower performance than those built with the other methods. (The Visual Studio compiler does not support the dialect of assembly used in the cpu-specific optimized files, so only the "generic" TARGET which is
written in pure C will get built. For the same reason it is not possible (and not necessary) to use -DDYNAMIC_ARCH=ON in a Visual Studio build) You may consider building for the 32-bit architecture using the GNU (MinGW) ABI.

####### 1. Install CMake at Windows

####### 2. Use CMake to generate Visual Studio solution files

# Do this from Powershell so cmake can find visual studio
cmake -G "Visual Studio 14 Win64" -DCMAKE_BUILD_TYPE=Release .
Build the solution at Visual Studio

Note that this step depends on perl, so you'll need to install perl for windows, and put perl on your path so VS can start perl (http://stackoverflow.com/questions/3051049/active-perl-installation-on-windows-operating-system).

Step 2 will build the OpenBLAS solution, open it in VS, and build the projects. Note that the dependencies do not seem to be automatically configured: if you try to build libopenblas directly, it will fail with a message saying that some .obj files aren't found, but if you build the projects libopenblas depends on before building libopenblas, the build will succeed.

Build OpenBLAS for Universal Windows Platform

OpenBLAS can be built for use on the Universal Windows Platform using a two step process since commit c66b842.

####### 1. Follow steps 1 and 2 above to build the Visual Studio solution files for Windows. This builds the helper executables which are required when building the OpenBLAS Visual Studio solution files for UWP in step 2.

####### 2. Remove the generated CMakeCache.txt and CMakeFiles directory from the OpenBLAS source directory and re-run CMake with the following options:

# do this to build UWP compatible solution files
cmake -G "Visual Studio 14 Win64" -DCMAKE_SYSTEM_NAME=WindowsStore -DCMAKE_SYSTEM_VERSION="10.0" -DCMAKE_SYSTEM_PROCESSOR=AMD64 -DVS_WINRT_COMPONENT=TRUE -DCMAKE_BUILD_TYPE=Release .

####### Build the solution with Visual Studio

This will build the OpenBLAS binaries with the required settings for use with UWP.

2. GNU (MinGW) ABI

The resulting library can be used in Visual Studio, but it can only be linked dynamically. This configuration has not been thoroughly tested and should be considered experimental.

Incompatible x86 calling conventions

Due to incompatibilities between the calling conventions of MinGW and Visual Studio you will need to make the following modifications ( 32-bit only ):

  1. Use the newer GCC 4.7.0. The older GCC (<4.7.0) has an ABI incompatibility for returning aggregate structures larger than 8 bytes with MSVC.
Build OpenBLAS on Windows OS
  1. Install the MinGW (GCC) compiler suite, either 32-bit (http://www.mingw.org/) or 64-bit (http://mingw-w64.sourceforge.net/). Be sure to install its gfortran package as well (unless you really want to build the BLAS part of OpenBLAS only) and check that gcc and gfortran are the same version – mixing compilers from different sources or release versions can lead to strange error messages in the linking stage. In addition, please install MSYS with MinGW.
  2. Build OpenBLAS in the MSYS shell. Usually, you can just type "make". OpenBLAS will detect the compiler and CPU automatically.
  3. After the build is complete, OpenBLAS will generate the static library "libopenblas.a" and the shared dll library "libopenblas.dll" in the folder. You can type "make PREFIX=/your/installation/path install" to install the library to a certain location.

!!! note
We suggest using official MinGW or MinGW-w64 compilers. A user reported that s/he met Unhandled exception by other compiler suite. https://groups.google.com/forum/#!topic/openblas-users/me2S4LkE55w

Note also that older versions of the alternative builds of mingw-w64 available through http://www.msys2.org may contain a defect that leads to a compilation failure accompanied by the error message

<command-line>:0:4: error: expected identifier or '(' before numeric constant

If you encounter this, please upgrade your msys2 setup or see https://github.com/OpenMathLib/OpenBLAS/issues/1503 for a workaround.

Generate import library (before 0.2.10 version)
  1. First, you will need to have the lib.exe tool in the Visual Studio command prompt.
  2. Open the command prompt and type cd OPENBLAS_TOP_DIR/exports, where OPENBLAS_TOP_DIR is the main folder of your OpenBLAS installation.
  3. For a 32-bit library, type lib /machine:i386 /def:libopenblas.def. For 64-bit, type lib /machine:X64 /def:libopenblas.def.
  4. This will generate the import library "libopenblas.lib" and the export library "libopenblas.exp" in OPENBLAS_TOP_DIR/exports. Although these two files have the same name, they are totally different.
Generate import library (0.2.10 and after version)
  1. OpenBLAS already generated the import library "libopenblas.dll.a" for "libopenblas.dll".
generate windows native PDB files from gcc/gfortran build

Tool to do so is available at https://github.com/rainers/cv2pdb

Use OpenBLAS .dll library in Visual Studio
  1. Copy the import library (before 0.2.10: "OPENBLAS_TOP_DIR/exports/libopenblas.lib", 0.2.10 and after: "OPENBLAS_TOP_DIR/libopenblas.dll.a") and .dll library "libopenblas.dll" into the same folder(The folder of your project that is going to use the BLAS library. You may need to add the libopenblas.dll.a to the linker input list: properties->Linker->Input).
  2. Please follow the documentation about using third-party .dll libraries in MS Visual Studio 2008 or 2010. Make sure to link against a library for the correct architecture. For example, you may receive an error such as "The application was unable to start correctly (0xc000007b)" which typically indicates a mismatch between 32/64-bit libraries.

!!! note
If you need CBLAS, you should include cblas.h in /your/installation/path/include in Visual Studio. Please read this page.

Limitations
  • Both static and dynamic linking are supported with MinGW. With Visual Studio, however, only dynamic linking is supported and so you should use the import library.
  • Debugging from Visual Studio does not work because MinGW and Visual Studio have incompatible formats for debug information (PDB vs. DWARF/STABS). You should either debug with GDB on the command-line or with a visual frontend, for instance Eclipse or Qt Creator.

Windows on Arm

Prerequisites

Following tools needs to be installed

1. Download and install clang for windows on arm

Find the latest LLVM build for WoA from LLVM release page

E.g: LLVM 12 build for WoA64 can be found here

Run the LLVM installer and ensure that LLVM is added to environment PATH.

2. Download and install classic flang for windows on arm

Classic flang is the only available FORTRAN compiler for windows on arm for now and a pre-release build can be found here

There is no installer for classic flang and the zip package can be extracted and the path needs to be added to environment PATH.

E.g: on PowerShell

$env:Path += ";C:\flang_woa\bin"
Build

The following steps describe how to build the static library for OpenBLAS with and without LAPACK

1. Build OpenBLAS static library with BLAS and LAPACK routines with Make

Following command can be used to build OpenBLAS static library with BLAS and LAPACK routines

$ make CC="clang-cl" HOSTCC="clang-cl" AR="llvm-ar" BUILD_WITHOUT_LAPACK=0 NOFORTRAN=0 DYNAMIC_ARCH=0 TARGET=ARMV8 ARCH=arm64 BINARY=64 USE_OPENMP=0 PARALLEL=1 RANLIB="llvm-ranlib" MAKE=make F_COMPILER=FLANG FC=FLANG FFLAGS_NOOPT="-march=armv8-a -cpp" FFLAGS="-march=armv8-a -cpp" NEED_PIC=0 HOSTARCH=arm64 libs netlib
2. Build static library with BLAS routines using CMake

Classic flang has compatibility issues with cmake hence only BLAS routines can be compiled with CMake

$ mkdir build
$ cd build
$ cmake ..  -G Ninja -DCMAKE_C_COMPILER=clang -DBUILD_WITHOUT_LAPACK=1 -DNOFORTRAN=1 -DDYNAMIC_ARCH=0 -DTARGET=ARMV8 -DARCH=arm64 -DBINARY=64 -DUSE_OPENMP=0 -DCMAKE_SYSTEM_PROCESSOR=ARM64 -DCMAKE_CROSSCOMPILING=1 -DCMAKE_SYSTEM_NAME=Windows
$ cmake --build . --config Release
getarch.exe execution error

If you notice that platform-specific headers by getarch.exe are not generated correctly, It could be due to a known debug runtime DLL issue for arm64 platforms. Please check out link for the workaround.

MinGW import library

Microsoft Windows has this thing called "import libraries". You don't need it in MinGW because the ld linker from GNU Binutils is smart, but you may still want it for whatever reason.

Make the .def

Import libraries are compiled from a list of what symbols to use, .def. This should be already in your exports directory: cd OPENBLAS_TOP_DIR/exports.

Making a MinGW import library

MinGW import libraries have the suffix .a, same as static libraries. (It's actually more common to do .dll.a...)

You need to first prepend libopenblas.def with a line LIBRARY libopenblas.dll:

cat <(echo "LIBRARY libopenblas.dll") libopenblas.def > libopenblas.def.1
mv libopenblas.def.1 libopenblas.def

Now it probably looks like:

LIBRARY libopenblas.dll
EXPORTS
   caxpy=caxpy_  @1
   caxpy_=caxpy_  @2
       ...

Then, generate the import library: dlltool -d libopenblas.def -l libopenblas.a

Again, there is basically no point in making an import library for use in MinGW. It actually slows down linking.

Making a MSVC import library

Unlike MinGW, MSVC absolutely requires an import library. Now the C ABI of MSVC and MinGW are actually identical, so linking is actually okay. (Any incompatibility in the C ABI would be a bug.)

The import libraries of MSVC have the suffix .lib. They are generated from a .def file using MSVC's lib.exe. See the MSVC instructions.

Notes
  • Always remember that MinGW is not the same as MSYS2 or Cygwin. MSYS2 and Cygwin are full POSIX environments with a lot of magic such as fork() and its own malloc(). MinGW, which builds on the normal Microsoft C Runtime, has none of that. Be clear about which one you are building for.

Android

Prerequisites

In addition to the Android NDK, you will need both Perl and a C compiler on the build host as these are currently
required by the OpenBLAS build environment.

Building with android NDK using clang compiler

Around version 11 Android NDKs stopped supporting gcc, so you would need to use clang to compile OpenBLAS. clang is supported from OpenBLAS 0.2.20 version onwards. See below sections on how to build with clang for ARMV7 and ARMV8 targets. The same basic principles as described below for ARMV8 should also apply to building an x86 or x86_64 version (substitute something like NEHALEM for the target instead of ARMV8 and replace all the aarch64 in the toolchain paths obviously)
"Historic" notes:
Since version 19 the default toolchain is provided as a standalone toolchain, so building one yourself following building a standalone toolchain should no longer be necessary.
If you want to use static linking with an old NDK version older than about r17, you need to choose an API level below 23 currently due to NDK bug 272 (https://github.com/android-ndk/ndk/issues/272 , the libc.a lacks a definition of stderr) that will probably be fixed in r17 of the NDK.

Build ARMV7 with clang

## Set path to ndk-bundle
export NDK_BUNDLE_DIR=/path/to/ndk-bundle

## Set the PATH to contain paths to clang and arm-linux-androideabi-* utilities
export PATH=${NDK_BUNDLE_DIR}/toolchains/arm-linux-androideabi-4.9/prebuilt/linux-x86_64/bin:${NDK_BUNDLE_DIR}/toolchains/llvm/prebuilt/linux-x86_64/bin:$PATH

## Set LDFLAGS so that the linker finds the appropriate libgcc
export LDFLAGS="-L${NDK_BUNDLE_DIR}/toolchains/arm-linux-androideabi-4.9/prebuilt/linux-x86_64/lib/gcc/arm-linux-androideabi/4.9.x"

## Set the clang cross compile flags
export CLANG_FLAGS="-target arm-linux-androideabi -marm -mfpu=vfp -mfloat-abi=softfp --sysroot ${NDK_BUNDLE_DIR}/platforms/android-23/arch-arm -gcc-toolchain ${NDK_BUNDLE_DIR}/toolchains/arm-linux-androideabi-4.9/prebuilt/linux-x86_64/"

#OpenBLAS Compile
make TARGET=ARMV7 ONLY_CBLAS=1 AR=ar CC="clang ${CLANG_FLAGS}" HOSTCC=gcc ARM_SOFTFP_ABI=1 -j4

On a Mac, it may also be necessary to give the complete path to the ar utility in the make command above, like so:

AR=${NDK_BUNDLE_DIR}/toolchains/arm-linux-androideabi-4.9/prebuilt/darwin-x86_64/bin/arm-linux-androideabi-gcc-ar

otherwise you may get a linker error complaining about a "malformed archive header name at 8" when the native OSX ar command was invoked instead.

Build ARMV8 with clang

## Set path to ndk-bundle
export NDK_BUNDLE_DIR=/path/to/ndk-bundle/

## Export PATH to contain directories of clang and aarch64-linux-android-* utilities
export PATH=${NDK_BUNDLE_DIR}/toolchains/aarch64-linux-android-4.9/prebuilt/linux-x86_64/bin/:${NDK_BUNDLE_DIR}/toolchains/llvm/prebuilt/linux-x86_64/bin:$PATH

## Setup LDFLAGS so that loader can find libgcc and pass -lm for sqrt
export LDFLAGS="-L${NDK_BUNDLE_DIR}/toolchains/aarch64-linux-android-4.9/prebuilt/linux-x86_64/lib/gcc/aarch64-linux-android/4.9.x -lm"

## Setup the clang cross compile options
export CLANG_FLAGS="-target aarch64-linux-android --sysroot ${NDK_BUNDLE_DIR}/platforms/android-23/arch-arm64 -gcc-toolchain ${NDK_BUNDLE_DIR}/toolchains/aarch64-linux-android-4.9/prebuilt/linux-x86_64/"

## Compile
make TARGET=ARMV8 ONLY_CBLAS=1 AR=ar CC="clang ${CLANG_FLAGS}" HOSTCC=gcc -j4

Note: Using TARGET=CORTEXA57 in place of ARMV8 will pick up better optimized routines. Implementations for CORTEXA57 target is compatible with all other armv8 targets.

Note: For NDK 23b, something as simple as

export PATH=/opt/android-ndk-r23b/toolchains/llvm/prebuilt/linux-x86_64/bin/:$PATH
make HOSTCC=gcc CC=/opt/android-ndk-r23b/toolchains/llvm/prebuilt/linux-x86_64/bin/aarch64-linux-android31-clang ONLY_CBLAS=1 TARGET=ARMV8

appears to be sufficient on Linux.

Alternative script which was tested on OSX with NDK(21.3.6528147)

This script will build openblas for 3 architecture (ARMV7,ARMV8,X86) and put them with sudo make install to /opt/OpenBLAS/lib

export NDK=YOUR_PATH_TO_SDK/Android/sdk/ndk/21.3.6528147
export TOOLCHAIN=$NDK/toolchains/llvm/prebuilt/darwin-x86_64

make clean
make \
    TARGET=ARMV7 \
    ONLY_CBLAS=1 \
    CC="$TOOLCHAIN"/bin/armv7a-linux-androideabi21-clang \
    AR="$TOOLCHAIN"/bin/arm-linux-androideabi-ar \
    HOSTCC=gcc \
    ARM_SOFTFP_ABI=1 \
    -j4
sudo make install

make clean
make \
    TARGET=CORTEXA57 \
    ONLY_CBLAS=1 \
    CC=$TOOLCHAIN/bin/aarch64-linux-android21-clang \
    AR=$TOOLCHAIN/bin/aarch64-linux-android-ar \
    HOSTCC=gcc \
    -j4
sudo make install

make clean
make \
    TARGET=ATOM \
    ONLY_CBLAS=1 \
    CC="$TOOLCHAIN"/bin/i686-linux-android21-clang \
    AR="$TOOLCHAIN"/bin/i686-linux-android-ar \
    HOSTCC=gcc \
    ARM_SOFTFP_ABI=1 \
    -j4
sudo make install

## This will build for x86_64 
make clean
make \
    TARGET=ATOM BINARY=64\
    ONLY_CBLAS=1 \
    CC="$TOOLCHAIN"/bin/x86_64-linux-android21-clang \
    AR="$TOOLCHAIN"/bin/x86_64-linux-android-ar \
    HOSTCC=gcc \
    ARM_SOFTFP_ABI=1 \
    -j4
sudo make install

Also you can find full list of target architectures in TargetList.txt

anything below this line should be irrelevant nowadays unless you need to perform software archeology

Building OpenBLAS with very old gcc-based versions of the NDK, without Fortran

The prebuilt Android NDK toolchains do not include Fortran, hence parts like LAPACK cannot be built. You can still build OpenBLAS without it. For instructions on how to build OpenBLAS with Fortran, see the next section.

To use easily the prebuilt toolchains, follow building a standalone toolchain for your desired architecture.
This would be arm-linux-androideabi-gcc-4.9 for ARMV7 and aarch64-linux-android-gcc-4.9 for ARMV8.

You can build OpenBLAS (0.2.19 and earlier) with:

## Add the toolchain to your path
export PATH=/path/to/standalone-toolchain/bin:$PATH

## Build without Fortran for ARMV7
make TARGET=ARMV7 HOSTCC=gcc CC=arm-linux-androideabi-gcc NOFORTRAN=1 libs
## Build without Fortran for ARMV8
make TARGET=ARMV8 BINARY=64 HOSTCC=gcc CC=aarch64-linux-android-gcc NOFORTRAN=1 libs

Since we are cross-compiling, we make the libs recipe, not all. Otherwise you will get errors when trying to link/run tests as versions up to and including 0.2.19 cannot build a shared library for Android.

From 0.2.20 on, you should leave off the "libs" to get a full build, and you may want to use the softfp ABI instead of the deprecated hardfp one on ARMV7 so you would use

## Add the toolchain to your path
export PATH=/path/to/standalone-toolchain/bin:$PATH

## Build without Fortran for ARMV7
make TARGET=ARMV7 ARM_SOFTFP_ABI=1 HOSTCC=gcc CC=arm-linux-androideabi-gcc NOFORTRAN=1
## Build without Fortran for ARMV8
make TARGET=ARMV8 BINARY=64 HOSTCC=gcc CC=aarch64-linux-android-gcc NOFORTRAN=1

If you get an error about stdio.h not being found, you need to specify your sysroot in the CFLAGS argument to make like
CFLAGS=--sysroot=$NDK/platforms/android-16/arch-arm
When you are done, install OpenBLAS into the desired directory. Be sure to also use all command line options
here that you specified for building, otherwise errors may occur as it tries to install things you did not build:

make PREFIX=/path/to/install-dir TARGET=... install

Building OpenBLAS with Fortran

Instructions on how to build the GNU toolchains with Fortran can be found here. The Releases section provides prebuilt versions, use the standalone one.

You can build OpenBLAS with:

## Add the toolchain to your path
export PATH=/path/to/standalone-toolchain-with-fortran/bin:$PATH

## Build with Fortran for ARMV7
make TARGET=ARMV7 HOSTCC=gcc CC=arm-linux-androideabi-gcc FC=arm-linux-androideabi-gfortran libs
## Build with LAPACK for ARMV8
make TARGET=ARMV8 BINARY=64 HOSTCC=gcc CC=aarch64-linux-android-gcc FC=aarch64-linux-android-gfortran libs

As mentioned above you can leave off the libs argument here when building 0.2.20 and later, and you may want to add ARM_SOFTFP_ABI=1 when building for ARMV7.

Linking OpenBLAS (0.2.19 and earlier) for ARMV7

If you are using ndk-build, you need to set the ABI to hard floating points in your Application.mk:

APP_ABI := armeabi-v7a-hard

This will set the appropriate flags for you. If you are not using ndk-build, you will want to add the following flags:

TARGET_CFLAGS += -mhard-float -D_NDK_MATH_NO_SOFTFP=1
TARGET_LDFLAGS += -Wl,--no-warn-mismatch -lm_hard

From 0.2.20 on, it is also possible to build for the softfp ABI by specifying ARM_SOFTFP_ABI=1 during the build.
In that case, also make sure that all your dependencies are compiled with -mfloat-abi=softfp as well, as mixing
"hard" and "soft" floating point ABIs in a program will make it crash.

iPhone/iOS

As none of the current developers uses iOS, the following instructions are what was found to work in our Azure CI setup, but as far as we know this builds a fully working OpenBLAS for this platform.

Go to the directory where you unpacked OpenBLAS,and enter the following commands:

     CC=/Applications/Xcode_12.4.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/clang

CFLAGS= -O2 -Wno-macro-redefined -isysroot /Applications/Xcode_12.4.app/Contents/Developer/Platforms/iPhoneOS.platform/Developer/SDKs/iPhoneOS14.4.sdk -arch arm64 -miphoneos-version-min=10.0

make TARGET=ARMV8 DYNAMIC_ARCH=1 NUM_THREADS=32 HOSTCC=clang NOFORTRAN=1

Adjust MIN_IOS_VERSION as necessary for your installation, e.g. change the version number
to the minimum iOS version you want to target and execute this file to build the library.

MIPS

For mips targets you will need latest toolchains
P5600 - MTI GNU/Linux Toolchain
I6400, P6600 - IMG GNU/Linux Toolchain

The download link is below
(http://codescape-mips-sdk.imgtec.com/components/toolchain/2016.05-03/downloads.html)

You can use following commandlines for builds

IMG_TOOLCHAIN_DIR={full IMG GNU/Linux Toolchain path including "bin" directory -- for example, /opt/linux_toolchain/bin}
IMG_GCC_PREFIX=mips-img-linux-gnu
IMG_TOOLCHAIN=${IMG_TOOLCHAIN_DIR}/${IMG_GCC_PREFIX}

I6400 Build (n32):
make BINARY=32 BINARY32=1 CC=$IMG_TOOLCHAIN-gcc AR=$IMG_TOOLCHAIN-ar FC="$IMG_TOOLCHAIN-gfortran -EL -mabi=n32" RANLIB=$IMG_TOOLCHAIN-ranlib HOSTCC=gcc CFLAGS="-EL" FFLAGS=$CFLAGS LDFLAGS=$CFLAGS TARGET=I6400

I6400 Build (n64):
make BINARY=64 BINARY64=1 CC=$IMG_TOOLCHAIN-gcc AR=$IMG_TOOLCHAIN-ar FC="$IMG_TOOLCHAIN-gfortran -EL" RANLIB=$IMG_TOOLCHAIN-ranlib HOSTCC=gcc CFLAGS="-EL" FFLAGS=$CFLAGS LDFLAGS=$CFLAGS TARGET=I6400

P6600 Build (n32):
make BINARY=32 BINARY32=1 CC=$IMG_TOOLCHAIN-gcc AR=$IMG_TOOLCHAIN-ar FC="$IMG_TOOLCHAIN-gfortran -EL -mabi=n32" RANLIB=$IMG_TOOLCHAIN-ranlib HOSTCC=gcc CFLAGS="-EL" FFLAGS=$CFLAGS LDFLAGS=$CFLAGS TARGET=P6600

P6600 Build (n64):
make BINARY=64 BINARY64=1 CC=$IMG_TOOLCHAIN-gcc AR=$IMG_TOOLCHAIN-ar FC="$IMG_TOOLCHAIN-gfortran -EL" RANLIB=$IMG_TOOLCHAIN-ranlib HOSTCC=gcc CFLAGS="-EL" FFLAGS="$CFLAGS" LDFLAGS="$CFLAGS" TARGET=P6600

MTI_TOOLCHAIN_DIR={full MTI GNU/Linux Toolchain path including "bin" directory -- for example, /opt/linux_toolchain/bin}
MTI_GCC_PREFIX=mips-mti-linux-gnu
MTI_TOOLCHAIN=${IMG_TOOLCHAIN_DIR}/${IMG_GCC_PREFIX}

P5600 Build:

make BINARY=32 BINARY32=1 CC=$MTI_TOOLCHAIN-gcc AR=$MTI_TOOLCHAIN-ar FC="$MTI_TOOLCHAIN-gfortran -EL"    RANLIB=$MTI_TOOLCHAIN-ranlib HOSTCC=gcc CFLAGS="-EL" FFLAGS=$CFLAGS LDFLAGS=$CFLAGS TARGET=P5600

FreeBSD

You will need to install the following tools from the FreeBSD ports tree:

  • lang/gcc [1]
  • lang/perl5.12
  • ftp/curl
  • devel/gmake
  • devel/patch

To compile run the command:

$ gmake CC=gcc46 FC=gfortran46

Note that you need to build with GNU make and manually specify the compiler, otherwhise gcc 4.2 from the base system would be used.

[1]: Removal of Fortran from the FreeBSD base system

pkg install openblas

see https://www.freebsd.org/ports/index.html

Cortex-M

Cortex-M is a widely used microcontroller that is present in a variety of industrial and consumer electronics.
A common variant of the Cortex-M is the STM32F4xx series. Here, we will give instructions for building for
the STM32F4xx.

First, install the embedded arm gcc compiler from the arm website. Then, create the following toolchain file and build as follows.

# cmake .. -G Ninja -DCMAKE_C_COMPILER=arm-none-eabi-gcc -DCMAKE_TOOLCHAIN_FILE:PATH="toolchain.cmake" -DNOFORTRAN=1 -DTARGET=ARMV5 -DEMBEDDED=1

set(CMAKE_SYSTEM_NAME Generic)
set(CMAKE_SYSTEM_PROCESSOR arm)

set(CMAKE_C_COMPILER "arm-none-eabi-gcc.exe")
set(CMAKE_CXX_COMPILER "arm-none-eabi-g++.exe")

set(CMAKE_EXE_LINKER_FLAGS "--specs=nosys.specs" CACHE INTERNAL "")

set(CMAKE_FIND_ROOT_PATH_MODE_PROGRAM NEVER)
set(CMAKE_FIND_ROOT_PATH_MODE_LIBRARY ONLY)
set(CMAKE_FIND_ROOT_PATH_MODE_INCLUDE ONLY)
set(CMAKE_FIND_ROOT_PATH_MODE_PACKAGE ONLY)

In your embedded application, the following functions need to be provided for OpenBLAS to work correctly:

void free(void* ptr);
void* malloc(size_t size);

!!! note
If you are developing for an embedded platform, it is your responsibility to make sure that the device has sufficient memory for malloc calls. Libmemory provides one implementation of malloc for embedded platforms.