Pardiso works when mkl_rt is dinamically loaded

laoyuer · Sep 27, 2017 · 1c422a5 · 1c422a5
1 parent f9f4884
commit 1c422a5
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Showing 13 changed files with 385 additions and 190 deletions.
diff --git a/CMakeLists.txt b/CMakeLists.txt
@@ -87,22 +87,6 @@ option (ENABLE_MKL_PARDISO "Enable MKL Pardiso solver" ON)
 message(STATUS "MKL Pardiso: ${ENABLE_MKL_PARDISO}")
 
 
-# Find linear system solvers
-# ---------------------------------------------
-if (ENABLE_MKL_PARDISO)
-	option(MKL_USE_SINGLE_DYNAMIC_LIBRARY "Use MKL single dynamic library interface" ON)
-	message(STATUS "MKL single dynamic library (SDL) ${MKL_USE_SINGLE_DYNAMIC_LIBRARY}")
-	if (NOT MKL_USE_SINGLE_DYNAMIC_LIBRARY)
-		option(MKL_USE_STATIC_LIBRARIES "Use MKL in static library interface" ON)
-		message(STATUS "MKL static library interface ${MKL_USE_STATIC_LIBRARIES}")
-		option(MKL_MULTI_THREADED "Use MKL multi threading in static library interface" ON)
-		message(STATUS "MKL multi threading ${MKL_MULTI_THREADED}")
-	endif()
-
-	# Find MKL Pardiso
-	find_package(MKL REQUIRED)
-endif()
-
 # Generate header file with the global options
 # ---------------------------------------------
 configure_file(${CMAKE_CURRENT_SOURCE_DIR}/configure/glob_opts.h.in
@@ -265,7 +249,6 @@ include_directories(${linsys_solvers_includes})
 
 
 add_library (osqpstatic STATIC ${osqp_src} ${osqp_headers} ${linsys_solvers})
-target_link_libraries(osqpstatic ${linsys_solvers_libraries})
 
 
 if (MATLAB)
@@ -283,7 +266,6 @@ if (NOT PYTHON AND NOT MATLAB)
     # Create osqp shared library
     # NB: Add all the linear system solvers here
     add_library (osqp SHARED ${osqp_src} ${osqp_headers} ${linsys_solvers})
-    target_link_libraries(osqp ${linsys_solvers_libraries})
 
     # Create demo executable (linked to static library)
     add_executable (osqp_demo ${PROJECT_SOURCE_DIR}/examples/osqp_demo.c)

diff --git a/configure/cmake/FindMKL.cmake b/configure/cmake/FindMKL.cmake
diff --git a/configure/glob_opts.h.in b/configure/glob_opts.h.in
@@ -106,17 +106,6 @@ typedef float c_float;                /* for numerical values  */
 #endif
 
 
-#if EMBEDDED != 1
-
-#include <math.h>
-#ifndef DFLOAT // Doubles
-#define c_sqrt sqrt
-#else         // Floats
-#define c_sqrt sqrtf
-#endif
-
-#endif // end EMBEDDED
-
 
 /* Use customized constants -----------------------------------------------   */
 #ifndef OSQP_NULL
@@ -147,6 +136,18 @@ typedef float c_float;                /* for numerical values  */
 
 /* Use customized functions -----------------------------------------------   */
 
+#if EMBEDDED != 1
+
+#include <math.h>
+#ifndef DFLOAT // Doubles
+#define c_sqrt sqrt
+#else         // Floats
+#define c_sqrt sqrtf
+#endif
+
+#endif // end EMBEDDED
+
+
 #ifdef PRINTING
 #include <stdio.h>
 #include <string.h>

diff --git a/interfaces/python/tests/general/big_prob.py b/interfaces/python/tests/general/big_prob.py
@@ -19,8 +19,8 @@
 l = -1 * np.ones(n)
 u = 1 * np.ones(n)
 
-l += 10
-u += 10
+# l += 10
+# u += 10
 
 # l *= 1000
 # u *= 1000
@@ -44,9 +44,9 @@
 # q = q
 
 # Test
-rho = 10.
+rho = 0.1
 # rho=10.0
-q /= 100
+# q /= 100
 # P *= 100
 # q *= 2000
 
@@ -62,17 +62,18 @@
              'scaling': True,
              'scaling_norm': -1,
              'max_iter': 2500,
-             'verbose': True
+             'verbose': True,
+             'linsys_solver': 2
              }
 
 qp = mpbpy.QuadprogProblem(P, q, A, l, u)
-res_gurobi = qp.solve(solver=mpbpy.GUROBI, verbose=True)
+res_gurobi = qp.solve(solver=mpbpy.GUROBI, verbose=False)
 # res_purepy = qp.solve(solver=mpbpy.OSQP_PUREPY, **osqp_opts)
 # res_osqp = qp.solve(solver=mpbpy.OSQP, **osqp_opts)
-
-model = osqppurepy.OSQP()
-model.setup(P=P, q=q, A=A, l=l, u=u, **osqp_opts)
-res_osqppurepy = model.solve()
+#
+# model = osqppurepy.OSQP()
+# model.setup(P=P, q=q, A=A, l=l, u=u, **osqp_opts)
+# res_osqppurepy = model.solve()
 
 model = osqp.OSQP()
 model.setup(P=P, q=q, A=A, l=l, u=u, **osqp_opts)
@@ -83,20 +84,20 @@
 if res_gurobi.status == 'optimal':
     print("Difference Purepy vs Gurobi")
     print("  - primal = %.4f" %
-          (np.linalg.norm(res_gurobi.x - res_osqppurepy.x) /
+          (np.linalg.norm(res_gurobi.x - res_osqp.x) /
            np.linalg.norm(res_gurobi.x)))
     print("  - dual = %.4f" %
-          (np.linalg.norm(res_gurobi.y - res_osqppurepy.y) /
+          (np.linalg.norm(res_gurobi.y - res_osqp.y) /
            np.linalg.norm(res_gurobi.y)))
 
 
 # Solve with SCS
-import cvxpy
-x = cvxpy.Variable(n)
-objective = cvxpy.Minimize(cvxpy.quad_form(x, P) + q * x)
-constraints = [l <= A * x, A * x <= u]
-problem = cvxpy.Problem(objective, constraints)
-problem.solve(solver=cvxpy.SCS, verbose=True)
+# import cvxpy
+# x = cvxpy.Variable(n)
+# objective = cvxpy.Minimize(cvxpy.quad_form(x, P) + q * x)
+# constraints = [l <= A * x, A * x <= u]
+# problem = cvxpy.Problem(objective, constraints)
+# problem.solve(solver=cvxpy.SCS, verbose=True)
 
 
 # # Store optimal values

diff --git a/lin_sys/CMakeLists.txt b/lin_sys/CMakeLists.txt
@@ -1,5 +1,9 @@
 # Add subdirectory for each linear systems solver
 
+# Include this directory for library handler
+# NB Needed for subfolders
+include_directories(${CMAKE_CURRENT_SOURCE_DIR})
+
 # Direct solver
 add_subdirectory(direct)
 
@@ -9,10 +13,13 @@ add_subdirectory(direct)
 
 # Combine solvers
 # TODO: Add indirect ones
-set(linsys_solvers ${direct_linsys_solvers} PARENT_SCOPE)
-
-# Combine solvers external libraries
-set(linsys_solvers_libraries ${direct_linsys_solvers_libraries} PARENT_SCOPE)
+set(linsys_solvers
+    ${CMAKE_CURRENT_SOURCE_DIR}/LibraryHandler.c
+    ${CMAKE_CURRENT_SOURCE_DIR}/LibraryHandler.h
+    ${direct_linsys_solvers}
+    PARENT_SCOPE)
 
 # Combine solvers external libraries
-set(linsys_solvers_includes ${direct_linsys_solvers_includes} PARENT_SCOPE)
+set(linsys_solvers_includes
+    ${direct_linsys_solvers_includes}
+    PARENT_SCOPE)