Installing precompiled package

PIQP can be directly installed running the following commands

websave('install_piqp.m','https://raw.githubusercontent.com/PREDICT-EPFL/piqp/main/interfaces/matlab/install_piqp.m');
install_piqp

The prebuilt packages are built without OpenMP, i.e., the sparse_multistage_parallel KKT solver backend is not available. To use it, PIQP has to be built from source with OpenMP. See Multithreading for details.

Building and Installing from Source

To build PIQP it is required to have CMake, Eigen 3.3.4+ and a compatible compiler like GCC, Clang, or Visual Studio with C++ extensions on Windows installed. CMake and a compatible compiler should already be installed on most systems. The (optional) KKT solver backend sparse_multistage needs the additional dependency Blasfeo.

Installing Eigen

on macOS via Homebrew

brew install eigen

on Ubuntu

sudo apt install libeigen3-dev

on Windows via Chocolatey

choco install eigen

via conda

conda install -c conda-forge eigen

building from source

# clone Eigen
git clone https://gitlab.com/libeigen/eigen.git eigen
cd eigen
git checkout 3.4.0

# build Eigen
mkdir build
cd build
cmake .. -DCMAKE_BUILD_TYPE=Release
cmake --build .

# install Eigen
cmake --install .

Installing Blasfeo (optional)

via conda

conda install -c conda-forge blasfeo

Blasfeo installed via conda is a dynamic library and not static. Additionally, it is never build with the X64_INTEL_SKYLAKE_X target. This means if you care about static linkage or running an x86-64 CPU with AVX512 support, you might lose some performance, and building from source is recommended.

building from source (unix only)

# clone Blasfeo
git clone https://github.com/giaf/blasfeo.git blasfeo
cd blasfeo

# build Blasfeo
mkdir build
cd build
# -DTARGET=X64_INTEL_SKYLAKE_X    on x86_64 CPUs with AVX512 support (Intel Skylake / AMD Zen5 or later)
# -DTARGET=X64_INTEL_HASWELL      on x86_64 CPUs with AVX2 support (Intel Haswell / AMD Zen or later)
# -DTARGET=X64_INTEL_SANDY_BRIDGE on x86_64 CPUs with AVX support (Intel Sandy-Bridge or later)
# -DTARGET=X64_INTEL_CORE         on x86_64 CPUs with SSE3 support (Intel Core or later)
# -DTARGET=X64_AMD_BULLDOZER      on x86_64 CPUs with AVX and FMA support (AMD Bulldozer or later)
# -DTARGET=ARMV8A_APPLE_M1        on ARMv8A CPUs optimized for Apple M1 or later
# -DTARGET=ARMV8A_ARM_CORTEX_A76  on ARMv8A CPUs optimized for ARM Cortex A76 (e.g. Raspberry Pi 5) 
# -DTARGET=ARMV8A_ARM_CORTEX_A73  on ARMv8A CPUs optimized for ARM Cortex A73
# for more targets see https://github.com/giaf/blasfeo/blob/master/CMakeLists.txt#L55
cmake .. -DCMAKE_BUILD_TYPE=Release -DTARGET=X64_INTEL_HASWELL
cmake --build .

# install Blasfeo
cmake --install .

Building and Installing PIQP

• Clone PIQP from Github

  git clone https://github.com/PREDICT-EPFL/piqp.git
  

• Build the interface in Matlab by executing the following commands

  cd interfaces/matlab
  % to build with Blasfeo (needed for sparse_multistage backend)
  % setenv("CMAKE_ARGS", "-DBUILD_WITH_BLASFEO=ON")
  make_piqp
  

  This will build and package the Matlab interface into a piqp-matlab-{platform}64.tar.gz file. You can also directly add the interface to the search path in Matlab by running

  addpath(pwd)
  savepath