Trying osqp-cu12 wheels

Author: vineetbansal

.github/workflows/build_cuda.yml

@@ -1,4 +1,4 @@
-name: Build CUDA
+name: Build CUDA Linux
 
 on:
   push:

.github/workflows/build_cuda_windows.yml

@@ -1,4 +1,4 @@
-name: Build CUDA
+name: Build CUDA Windows
 
 on:
   push:
@@ -11,8 +11,8 @@ on:
       - master
 
 env:
-  CUDATOOLKIT_URL: https://developer.download.nvidia.com/compute/cuda/12.5.1/local_installers/cuda_12.5.1_555.85_windows.exe
-  CUDATOOLKIT_COMPONENTS: nvcc_12.5 cudart_12.5 cublas_dev_12.5 curand_dev_12.5 cusparse_dev_12.5 thrust_12.5 visual_studio_integration_12.5
+  CUDATOOLKIT_URL: https://developer.download.nvidia.com/compute/cuda/12.6.3/local_installers/cuda_12.6.3_561.17_windows.exe
+  CUDATOOLKIT_COMPONENTS: nvcc_12.6 cudart_12.6 cublas_dev_12.6 curand_dev_12.6 cusparse_dev_12.6 thrust_12.6 visual_studio_integration_12.6
 
 jobs:
   build_wheels:

.github/workflows/build_default.yml

@@ -79,7 +79,7 @@ jobs:
 
   publish_to_pypi:
     name: Publish wheels to PyPi
-    if: github.event_name == 'push' && startsWith(github.event.ref, 'refs/tags')
+    if: false
     needs: [build_sdist, build_wheels]
     runs-on: ubuntu-latest
     steps:

.github/workflows/build_mkl.yml

@@ -1,4 +1,4 @@
-name: Build MKL
+name: Build MKL Mac/Linux
 
 on:
   push:

.github/workflows/build_mkl_windows.yml

@@ -1,4 +1,4 @@
-name: Build MKL
+name: Build MKL Windows
 
 on:
   push:

.github/workflows/release.yml

@@ -8,9 +8,9 @@ repair-wheel-command = ""
 [tool.cibuildwheel.linux]
 before-all = [
   "yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/cuda-rhel7.repo",
-  "yum install -y cuda-toolkit-12-4"
+  "yum install -y cuda-toolkit-12-6"
 ]
-environment = { CMAKE_CUDA_COMPILER = "/usr/local/cuda-12.4/bin/nvcc" }
+environment = { CMAKE_CUDA_COMPILER = "/usr/local/cuda-12.6/bin/nvcc" }
 
 [tool.cibuildwheel.windows]
-environment = { CMAKE_CUDA_COMPILER = "C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.5/bin/nvcc.exe", CUDA_TOOLKIT_ROOT_DIR = "C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.5", CMAKE_GENERATOR_TOOLSET = "cuda=C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.5" }
+environment = { CMAKE_CUDA_COMPILER = "C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.6/bin/nvcc.exe", CUDA_TOOLKIT_ROOT_DIR = "C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.6", CMAKE_GENERATOR_TOOLSET = "cuda=C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.6" }

backend/cuda/cibuildwheel.toml

@@ -3,7 +3,7 @@ requires = ["scikit-build-core", "pybind11"]
 build-backend = "scikit_build_core.build"
 
 [project]
-name = "osqp-cuda"
+name = "osqp-cu12"
 dynamic = ["version"]
 description = "OSQP: The Operator Splitting QP Solver"
 requires-python = ">=3.8"

backend/cuda/pyproject.toml

@@ -0,0 +1,36 @@
+import osqp
+import numpy as np
+from scipy import sparse
+
+if __name__ == '__main__':
+    # Define problem data
+    P = sparse.csc_matrix([[4, 1], [1, 2]])
+    q = np.array([1, 1])
+    A = sparse.csc_matrix([[1, 1], [1, 0], [0, 1]])
+    l = np.array([1, 0, 0])
+    u = np.array([1, 0.7, 0.7])
+
+    # Create an OSQP object
+    prob = osqp.OSQP()
+
+    # Setup workspace
+    prob.setup(P, q, A, l, u)
+
+    # Solve problem
+    res = prob.solve()
+
+    # Update problem
+    # IMPORTANT: The sparsity structure of P/A should remain the same,
+    # so we only update Px and Ax
+    # (i.e. the actual data values at indices with nonzero values)
+    # NB: Update only upper triangular part of P
+    P_new = sparse.csc_matrix([[5, 1.5], [1.5, 1]])
+    A_new = sparse.csc_matrix([[1.2, 1.1], [1.5, 0], [0, 0.8]])
+    prob.update(Px=sparse.triu(P_new).data, Ax=A_new.data)
+
+    # Solve updated problem
+    res = prob.solve()
+
+    print('Status:', res.info.status)
+    print('Objective value:', res.info.obj_val)
+    print('Optimal solution x:', res.x)

examples/update_matrices.py

@@ -0,0 +1,33 @@
+import osqp
+import numpy as np
+from scipy import sparse
+
+if __name__ == '__main__':
+    # Define problem data
+    P = sparse.csc_matrix([[4, 1], [1, 2]])
+    q = np.array([1, 1])
+    A = sparse.csc_matrix([[1, 1], [1, 0], [0, 1]])
+    l = np.array([1, 0, 0])
+    u = np.array([1, 0.7, 0.7])
+
+    # Create an OSQP object
+    prob = osqp.OSQP()
+
+    # Setup workspace
+    prob.setup(P, q, A, l, u)
+
+    # Solve problem
+    res = prob.solve()
+
+    # Update problem
+    q_new = np.array([2, 3])
+    l_new = np.array([2, -1, -1])
+    u_new = np.array([2, 2.5, 2.5])
+    prob.update(q=q_new, l=l_new, u=u_new)
+
+    # Solve updated problem
+    res = prob.solve()
+
+    print('Status:', res.info.status)
+    print('Objective value:', res.info.obj_val)
+    print('Optimal solution x:', res.x)