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

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