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nvidia_cusolver_linear_system_solver_lu_decomposition.py

python

This quickstart demonstrates how to use the NVIDIA cuSOLVER library

15d ago64 linesNVIDIA/cuda-python
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nvidia_cusolver_linear_system_solver_lu_decomposition.py
1import numpy as np
2from cuda import cuda, cusolver
3
4def checkCudaErrors(result):
5    if result[0] != 0:
6        raise RuntimeError("CUDA error: " + str(result[0]))
7    if len(result) == 1:
8        return None
9    elif len(result) == 2:
10        return result[1]
11    else:
12        return result[1:]
13
14def main():
15    # Matrix A and Vector B
16    h_A = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float64)
17    h_B = np.array([5.0, 11.0], dtype=np.float64)
18    n = h_A.shape[0]
19
20    # Initialize CUDA
21    checkCudaErrors(cuda.cuInit(0))
22    device = checkCudaErrors(cuda.cuDeviceGet(0))
23    context = checkCudaErrors(cuda.cuCtxCreate(0, device))
24
25    # Create cuSOLVER handle
26    handle = checkCudaErrors(cusolver.cusolverDnCreate())
27
28    # Allocate device memory
29    d_A = checkCudaErrors(cuda.cuMemAlloc(h_A.nbytes))
30    d_B = checkCudaErrors(cuda.cuMemAlloc(h_B.nbytes))
31    d_Ipiv = checkCudaErrors(cuda.cuMemAlloc(n * np.dtype(np.int32).itemsize))
32    d_info = checkCudaErrors(cuda.cuMemAlloc(np.dtype(np.int32).itemsize))
33
34    # Copy data to device
35    checkCudaErrors(cuda.cuMemcpyHtoD(d_A, h_A.ctypes.data, h_A.nbytes))
36    checkCudaErrors(cuda.cuMemcpyHtoD(d_B, h_B.ctypes.data, h_B.nbytes))
37
38    # Workspace query for LU decomposition (getrf)
39    workspaceSize = checkCudaErrors(cusolver.cusolverDnDgetrf_bufferSize(handle, n, n, d_A, n))
40    d_workspace = checkCudaErrors(cuda.cuMemAlloc(workspaceSize))
41
42    # LU Factorization (A = P*L*U)
43    checkCudaErrors(cusolver.cusolverDnDgetrf(handle, n, n, d_A, n, d_workspace, d_Ipiv, d_info))
44
45    # Solve Ax = B (getrs)
46    checkCudaErrors(cusolver.cusolverDnDgetrs(handle, cusolver.cublasOperation_t.CUBLAS_OP_N, n, 1, d_A, n, d_Ipiv, d_B, n, d_info))
47
48    # Copy result back to host
49    h_X = np.empty_like(h_B)
50    checkCudaErrors(cuda.cuMemcpyDtoH(h_X.ctypes.data, d_B, h_B.nbytes))
51
52    print(f"Solution x: {h_X}")
53
54    # Cleanup
55    checkCudaErrors(cusolver.cusolverDnDestroy(handle))
56    checkCudaErrors(cuda.cuMemFree(d_A))
57    checkCudaErrors(cuda.cuMemFree(d_B))
58    checkCudaErrors(cuda.cuMemFree(d_Ipiv))
59    checkCudaErrors(cuda.cuMemFree(d_info))
60    checkCudaErrors(cuda.cuMemFree(d_workspace))
61    checkCudaErrors(cuda.cuCtxDestroy(context))
62
63if __name__ == "__main__":
64    main()