Add box constraint interface for dense backend

.github/workflows/ci-linux-osx-win-conda.yml

@@ -112,7 +112,7 @@ jobs:
         echo $(whereis ccache)
         echo $(which ccache)
         cd build
-        cmake .. -GNinja -DCMAKE_C_COMPILER_LAUNCHER=ccache -DCMAKE_CXX_COMPILER_LAUNCHER=ccache -DCHECK_RUNTIME_MALLOC:BOOL=ON -DCMAKE_CXX_STANDARD=${{ matrix.cxx_std }} -DCMAKE_INSTALL_PREFIX=${CONDA_PREFIX} -DCMAKE_BUILD_TYPE=${{ matrix.build_type }} -DBUILD_PYTHON_INTERFACE:BOOL=ON -DPYTHON_EXECUTABLE=$(which python3) -DBUILD_DOCUMENTATION:BOOL=ON -DINSTALL_DOCUMENTATION:BOOL=ON -DTEST_JULIA_INTERFACE:BOOL=ON -DOpenMP_ROOT=$CONDA_PREFIX
+        cmake .. -GNinja -DCMAKE_C_COMPILER_LAUNCHER=ccache -DCMAKE_CXX_COMPILER_LAUNCHER=ccache -DCHECK_RUNTIME_MALLOC:BOOL=ON -DCMAKE_CXX_STANDARD=${{ matrix.cxx_std }} -DCMAKE_INSTALL_PREFIX=${CONDA_PREFIX} -DCMAKE_BUILD_TYPE=${{ matrix.build_type }} -DBUILD_PYTHON_INTERFACE:BOOL=ON -DPYTHON_EXECUTABLE=$(which python3) -DBUILD_DOCUMENTATION:BOOL=ON -DINSTALL_DOCUMENTATION:BOOL=ON -DTEST_JULIA_INTERFACE:BOOL=ON -DBUILD_WITH_OPENMP_SUPPORT:BOOL=ON -DOpenMP_ROOT=$CONDA_PREFIX
 
     - name: Configure [Conda/Windows-2019]
       if: contains(matrix.os, 'windows-2019')
@@ -122,7 +122,7 @@ jobs:
         git submodule update --init
         mkdir build
         cd build
-        cmake .. -G"Visual Studio 16 2019" -T "ClangCl" -DCMAKE_GENERATOR_PLATFORM=x64 -DCMAKE_C_COMPILER_LAUNCHER=ccache -DCMAKE_CXX_COMPILER_LAUNCHER=ccache -DCMAKE_INSTALL_PREFIX=${CONDA_PREFIX}/Library -DCMAKE_BUILD_TYPE=${{ matrix.build_type }}  -DBUILD_PYTHON_INTERFACE:BOOL=ON -DPYTHON_SITELIB=${CONDA_PREFIX}/Lib/site-packages -DPYTHON_EXECUTABLE=${CONDA_PREFIX}/python.exe -DBUILD_DOCUMENTATION:BOOL=ON -DINSTALL_DOCUMENTATION:BOOL=ON
+        cmake .. -G"Visual Studio 16 2019" -T "ClangCl" -DCMAKE_GENERATOR_PLATFORM=x64 -DCMAKE_C_COMPILER_LAUNCHER=ccache -DCMAKE_CXX_COMPILER_LAUNCHER=ccache -DCMAKE_INSTALL_PREFIX=${CONDA_PREFIX}/Library -DCMAKE_BUILD_TYPE=${{ matrix.build_type }}  -DBUILD_PYTHON_INTERFACE:BOOL=ON -DPYTHON_SITELIB=${CONDA_PREFIX}/Lib/site-packages -DPYTHON_EXECUTABLE=${CONDA_PREFIX}/python.exe -DOpenMP_ROOT=$CONDA_PREFIX -DBUILD_WITH_OPENMP_SUPPORT:BOOL=OFF -DLINK_PYTHON_INTERFACE_TO_OPENMP:BOOL=ON -DBUILD_DOCUMENTATION:BOOL=ON -DINSTALL_DOCUMENTATION:BOOL=ON
 
     - name: Configure [Conda/Windows-latest]
       if: contains(matrix.os, 'windows-latest')
@@ -132,7 +132,7 @@ jobs:
         git submodule update --init
         mkdir build
         cd build
-        cmake .. -G"Visual Studio 17 2022" -T "v143" -DCMAKE_GENERATOR_PLATFORM=x64 -DCMAKE_C_COMPILER_LAUNCHER=ccache -DCMAKE_CXX_COMPILER_LAUNCHER=ccache -DCMAKE_INSTALL_PREFIX=${CONDA_PREFIX}/Library -DCMAKE_BUILD_TYPE=${{ matrix.build_type }}  -DBUILD_PYTHON_INTERFACE:BOOL=ON -DPYTHON_SITELIB=${CONDA_PREFIX}/Lib/site-packages -DPYTHON_EXECUTABLE=${CONDA_PREFIX}/python.exe -DBUILD_DOCUMENTATION:BOOL=ON -DINSTALL_DOCUMENTATION:BOOL=ON
+        cmake .. -G"Visual Studio 17 2022" -T "v143" -DCMAKE_GENERATOR_PLATFORM=x64 -DCMAKE_C_COMPILER_LAUNCHER=ccache -DCMAKE_CXX_COMPILER_LAUNCHER=ccache -DCMAKE_INSTALL_PREFIX=${CONDA_PREFIX}/Library -DCMAKE_BUILD_TYPE=${{ matrix.build_type }}  -DBUILD_PYTHON_INTERFACE:BOOL=ON -DPYTHON_SITELIB=${CONDA_PREFIX}/Lib/site-packages -DPYTHON_EXECUTABLE=${CONDA_PREFIX}/python.exe -DOpenMP_ROOT=$CONDA_PREFIX -DBUILD_WITH_OPENMP_SUPPORT:BOOL=ON -DLINK_PYTHON_INTERFACE_TO_OPENMP:BOOL=ON -DBUILD_DOCUMENTATION:BOOL=ON -DINSTALL_DOCUMENTATION:BOOL=ON
 
     - name: Build [Conda]
       shell: bash -l {0}

.gitmodules

@@ -7,3 +7,5 @@
 [submodule "external/cereal"]
 	path = external/cereal
 	url = https://github.com/USCiLab/cereal.git
+[submodule "cmake"]
+	url = https://github.com/jrl-umi3218/jrl-cmakemodules.git

CMakeLists.txt

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2022 INRIA
+# Copyright (c) 2022-2023 INRIA
 #
 
 cmake_minimum_required(VERSION 3.10)
@@ -48,7 +48,7 @@ project(${PROJECT_NAME} ${PROJECT_ARGS})
 
 include(${CMAKE_CURRENT_LIST_DIR}/cmake-module/ide.cmake)
 include(${CMAKE_CURRENT_LIST_DIR}/cmake-module/apple.cmake)
-if(APPLE) # Use the handmade approach
+if(APPLE OR WIN32) # Use the handmade approach
   set(CMAKE_MODULE_PATH ${CMAKE_CURRENT_LIST_DIR}/cmake/find-external/OpenMP
                         ${CMAKE_MODULE_PATH})
 elseif(UNIX)
@@ -78,7 +78,8 @@ option(BUILD_BINDINGS_WITH_AVX2_SUPPORT "Build the bindings with AVX2 support."
 option(BUILD_BINDINGS_WITH_AVX512_SUPPORT
        "Build the bindings with AVX512 support." ON)
 option(TEST_JULIA_INTERFACE "Run the julia examples as unittest" OFF)
-option(BUILD_WITH_OPENMP_SUPPORT "Build the library with the OpenMP support" ON)
+option(BUILD_WITH_OPENMP_SUPPORT "Build the library with the OpenMP support"
+       OFF)
 cmake_dependent_option(
   LINK_PYTHON_INTERFACE_TO_OPENMP "Link OpenMP to the Python interface" ON
   BUILD_WITH_OPENMP_SUPPORT OFF)

README.md

@@ -32,14 +32,16 @@ We are ready to integrate **ProxSuite** within other optimization ecosystems.
 **Proxsuite** is versatile, offering through a unified API advanced algorithms specialized for efficiently exploiting problem structures:
 
    - dense, sparse and matrix-free matrix factorization backends,
-   - advanced warm-starting options (e.g., equality-constrained initial guess, warm-start or cold-start options from previous results).
+   - advanced warm-starting options (e.g., equality-constrained initial guess, warm-start or cold-start options from previous results),
+   - dedicated features for handling more efficiently box constraints, or linear programs.
 
 **Proxsuite** is flexible:
 
    - header only,
    - C++ 14/17/20 compliant,
    - Python and Julia bindings for easy code prototyping without sacrificing performance.
 
+**Proxsuite** has a dedicated feature for solving batch of QPs.
 **Proxsuite** is extensible.
 **Proxsuite** is reliable and extensively tested, showing the best performances on the hardest problems of the literature.
 **Proxsuite** is supported and tested on Windows, Mac OS X, Unix and Linux.

benchmark/CMakeLists.txt

@@ -16,6 +16,7 @@ macro(proxsuite_benchmark bench_name)
 endmacro(proxsuite_benchmark)
 
 proxsuite_benchmark(timings-lp)
+proxsuite_benchmark(timings-box-constraints)
 
 if(BUILD_WITH_OPENMP_SUPPORT)
   proxsuite_benchmark(timings-parallel)

benchmark/timings-box-constraints.cpp

@@ -0,0 +1,127 @@
+//
+// Copyright (c) 2023 INRIA
+//
+#include <iostream>
+#include <proxsuite/proxqp/dense/dense.hpp>
+#include <proxsuite/proxqp/utils/random_qp_problems.hpp>
+
+using T = double;
+using I = long long;
+
+using namespace proxsuite;
+using namespace proxsuite::proxqp;
+
+int
+main(int /*argc*/, const char** /*argv*/)
+{
+  Timer<T> timer;
+  int smooth = 100;
+
+  T sparsity_factor = 0.75;
+  T eps_abs = T(1e-9);
+  T elapsed_time = 0.0;
+  proxqp::utils::rand::set_seed(1);
+  std::cout << "Dense QP" << std::endl;
+  for (proxqp::isize dim = 100; dim <= 1000; dim = dim + 100) {
+
+    proxqp::isize n_eq(dim / 2);
+    proxqp::isize n_in(dim / 2);
+    std::cout << "dim: " << dim << " n_eq: " << n_eq << " n_in: " << n_in
+              << " box: " << dim << std::endl;
+    T strong_convexity_factor(1.e-2);
+
+    proxqp::dense::Model<T> qp_random = proxqp::utils::dense_strongly_convex_qp(
+      dim, n_eq, n_in, sparsity_factor, strong_convexity_factor);
+    Eigen::Matrix<T, Eigen::Dynamic, 1> x_sol =
+      utils::rand::vector_rand<T>(dim);
+    Eigen::Matrix<T, Eigen::Dynamic, 1> delta(n_in);
+    for (proxqp::isize i = 0; i < n_in; ++i) {
+      delta(i) = utils::rand::uniform_rand();
+    }
+    qp_random.u = qp_random.C * x_sol + delta;
+    qp_random.b = qp_random.A * x_sol;
+    Eigen::Matrix<T, Eigen::Dynamic, 1> u_box(dim);
+    u_box.setZero();
+    Eigen::Matrix<T, Eigen::Dynamic, 1> l_box(dim);
+    l_box.setZero();
+    for (proxqp::isize i = 0; i < dim; ++i) {
+      T shift = utils::rand::uniform_rand();
+      u_box(i) = x_sol(i) + shift;
+      l_box(i) = x_sol(i) - shift;
+    }
+    using Mat =
+      Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic, Eigen::ColMajor>;
+    Mat C_enlarged(dim + n_in, dim);
+    C_enlarged.setZero();
+    C_enlarged.topLeftCorner(n_in, dim) = qp_random.C;
+    C_enlarged.bottomLeftCorner(dim, dim).diagonal().array() += 1.;
+    Eigen::Matrix<T, Eigen::Dynamic, 1> u_enlarged(n_in + dim);
+    Eigen::Matrix<T, Eigen::Dynamic, 1> l_enlarged(n_in + dim);
+    u_enlarged.head(n_in) = qp_random.u;
+    u_enlarged.tail(dim) = u_box;
+    l_enlarged.head(n_in) = qp_random.l;
+    l_enlarged.tail(dim) = l_box;
+
+    elapsed_time = 0.0;
+    timer.stop();
+    proxqp::dense::QP<T> qp{ dim, n_eq, n_in, true };
+    qp.settings.eps_abs = eps_abs;
+    qp.settings.eps_rel = 0;
+    qp.settings.initial_guess = InitialGuessStatus::NO_INITIAL_GUESS;
+    for (int j = 0; j < smooth; j++) {
+      timer.start();
+      qp.init(qp_random.H,
+              qp_random.g,
+              qp_random.A,
+              qp_random.b,
+              qp_random.C,
+              qp_random.l,
+              qp_random.u,
+              l_box,
+              u_box);
+      qp.solve();
+      timer.stop();
+      elapsed_time += timer.elapsed().user;
+      if (qp.results.info.pri_res > eps_abs ||
+          qp.results.info.dua_res > eps_abs) {
+        std::cout << "dual residual " << qp.results.info.dua_res
+                  << "; primal residual " << qp.results.info.pri_res
+                  << std::endl;
+        std::cout << "total number of iteration: " << qp.results.info.iter
+                  << std::endl;
+      }
+    }
+    std::cout << "timings QP with box constraints feature : \t"
+              << elapsed_time * 1e-3 / smooth << " ms" << std::endl;
+
+    elapsed_time = 0.0;
+    proxqp::dense::QP<T> qp_compare{ dim, n_eq, dim + n_in, false };
+    qp_compare.settings.eps_abs = eps_abs;
+    qp_compare.settings.eps_rel = 0;
+    qp_compare.settings.initial_guess = InitialGuessStatus::NO_INITIAL_GUESS;
+    for (int j = 0; j < smooth; j++) {
+      timer.start();
+      qp_compare.init(qp_random.H,
+                      qp_random.g,
+                      qp_random.A,
+                      qp_random.b,
+                      C_enlarged,
+                      l_enlarged,
+                      u_enlarged);
+      qp_compare.solve();
+      timer.stop();
+      elapsed_time += timer.elapsed().user;
+
+      if (qp_compare.results.info.pri_res > eps_abs ||
+          qp_compare.results.info.dua_res > eps_abs) {
+        std::cout << "dual residual " << qp_compare.results.info.dua_res
+                  << "; primal residual " << qp_compare.results.info.pri_res
+                  << std::endl;
+        std::cout << "total number of iteration: "
+                  << qp_compare.results.info.iter << std::endl;
+      }
+    }
+    std::cout << "timings QP without box constraints feature : \t"
+              << elapsed_time * 1e-3 / smooth << " ms" << std::endl;
+  }
+}

benchmark/timings-lp.cpp

@@ -71,7 +71,7 @@ main(int /*argc*/, const char** /*argv*/)
                   << std::endl;
       }
     }
-    std::cout << "timings LP: \t" << elapsed_time * 1e-3 / smooth << "ms"
+    std::cout << "timings LP: \t" << elapsed_time * 1e-3 / smooth << " ms"
               << std::endl;
 
     elapsed_time = 0.0;
@@ -101,7 +101,7 @@ main(int /*argc*/, const char** /*argv*/)
                   << qp_compare.results.info.iter << std::endl;
       }
     }
-    std::cout << "timings QP: \t" << elapsed_time * 1e-3 / smooth << "ms"
+    std::cout << "timings QP: \t" << elapsed_time * 1e-3 / smooth << " ms"
               << std::endl;
   }
 }

benchmark/timings-parallel.cpp

@@ -64,7 +64,7 @@ main(int /*argc*/, const char** /*argv*/)
     }
     timer.stop();
     std::cout << "time to generate and initialize std::vector of dense qps: \t"
-              << timer.elapsed().user * 1e-3 / smooth << "ms" << std::endl;
+              << timer.elapsed().user * 1e-3 / smooth << " ms" << std::endl;
 
     timer.start();
     for (int j = 0; j < smooth; j++) {
@@ -90,7 +90,7 @@ main(int /*argc*/, const char** /*argv*/)
     }
     timer.stop();
     std::cout << "time to generate and initialize dense:BatchQP: \t\t\t"
-              << timer.elapsed().user * 1e-3 / smooth << "ms" << std::endl;
+              << timer.elapsed().user * 1e-3 / smooth << " ms" << std::endl;
 
     for (int j = 0; j < smooth; j++) {
       std::vector<proxqp::sparse::QP<T, I>> qps;
@@ -118,7 +118,7 @@ main(int /*argc*/, const char** /*argv*/)
     }
     timer.stop();
     std::cout << "time to generate and initialize std::vector of sparse qps: \t"
-              << timer.elapsed().user * 1e-3 / smooth << "ms" << std::endl;
+              << timer.elapsed().user * 1e-3 / smooth << " ms" << std::endl;
 
     timer.start();
     for (int j = 0; j < smooth; j++) {
@@ -145,7 +145,7 @@ main(int /*argc*/, const char** /*argv*/)
     }
     timer.stop();
     std::cout << "time to generate and initialize sparse:BatchQP: \t\t\t"
-              << timer.elapsed().user * 1e-3 / smooth << "ms" << std::endl;
+              << timer.elapsed().user * 1e-3 / smooth << " ms" << std::endl;
   }
 
   {
@@ -203,7 +203,7 @@ main(int /*argc*/, const char** /*argv*/)
     }
     timer.stop();
     std::cout << "mean solve time in serial: \t\t\t"
-              << timer.elapsed().user * 1e-3 / smooth << "ms" << std::endl;
+              << timer.elapsed().user * 1e-3 / smooth << " ms" << std::endl;
 
     const size_t NUM_THREADS = (size_t)omp_get_max_threads();
 
@@ -216,7 +216,7 @@ main(int /*argc*/, const char** /*argv*/)
       timer.stop();
       std::cout << "mean solve time in parallel (" << num_threads
                 << " threads):\t" << timer.elapsed().user * 1e-3 / smooth
-                << "ms" << std::endl;
+                << " ms" << std::endl;
     }
 
     std::cout << "\nparallel using std::vector of dense QPs" << std::endl;
@@ -228,7 +228,7 @@ main(int /*argc*/, const char** /*argv*/)
       timer.stop();
       std::cout << "mean solve time in parallel (" << num_threads
                 << " threads):\t" << timer.elapsed().user * 1e-3 / smooth
-                << "ms" << std::endl;
+                << " ms" << std::endl;
     }
   }
 
@@ -289,7 +289,7 @@ main(int /*argc*/, const char** /*argv*/)
     }
     timer.stop();
     std::cout << "mean solve time in serial: \t\t\t"
-              << timer.elapsed().user * 1e-3 / smooth << "ms" << std::endl;
+              << timer.elapsed().user * 1e-3 / smooth << " ms" << std::endl;
 
     const size_t NUM_THREADS = (size_t)omp_get_max_threads();
 
@@ -302,7 +302,7 @@ main(int /*argc*/, const char** /*argv*/)
       timer.stop();
       std::cout << "mean solve time in parallel (" << num_threads
                 << " threads):\t" << timer.elapsed().user * 1e-3 / smooth
-                << "ms" << std::endl;
+                << " ms" << std::endl;
     }
 
     std::cout << "\nparallel using std::vector of sparse QPs" << std::endl;
@@ -314,7 +314,7 @@ main(int /*argc*/, const char** /*argv*/)
       timer.stop();
       std::cout << "mean solve time in parallel (" << num_threads
                 << " threads):\t" << timer.elapsed().user * 1e-3 / smooth
-                << "ms" << std::endl;
+                << " ms" << std::endl;
     }
   }
 }

bindings/python/CMakeLists.txt

@@ -2,6 +2,7 @@ if(UNIX)
   set(PYTHON_COMPONENTS Development.Module)
 endif()
 include(../../cmake-module/python.cmake)
+include(../../cmake-module/python-helpers.cmake)
 
 findpython(REQUIRED Development.Module)
 file(MAKE_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/external/pybind11)
@@ -136,4 +137,6 @@ foreach(python ${PYTHON_FILES})
   install(FILES "${CMAKE_CURRENT_SOURCE_DIR}/proxsuite/${python}"
           DESTINATION ${${PYWRAP}_INSTALL_DIR})
 endforeach(python)
+
+python_build_get_target(compile_pyc)
 add_dependencies(python ${compile_pyc})

bindings/python/src/expose-parallel.hpp

@@ -10,7 +10,7 @@
 #include <pybind11/stl.h>
 #include <pybind11/stl_bind.h> // For binding STL containers
 
-PYBIND11_MAKE_OPAQUE(std::vector<proxsuite::proxqp::dense::QP<double>>);
+PYBIND11_MAKE_OPAQUE(std::vector<proxsuite::proxqp::dense::QP<double>>)
 
 namespace proxsuite {
 namespace proxqp {