import numpy as np import sympy as sp import pystencils as ps def jacobi(dst, src): assert dst.spatial_dimensions == src.spatial_dimensions assert src.index_dimensions == 0 and dst.index_dimensions == 0 neighbors = [] for d in range(src.spatial_dimensions): neighbors += [src.neighbor(d, offset) for offset in (1, -1)] return ps.Assignment(dst.center, sp.Add(*neighbors) / len(neighbors)) def check_equivalence(assignments, src_arr): for openmp in (False, True): for vectorization in [False, {'assume_inner_stride_one': True}]: with_blocking = ps.create_kernel(assignments, cpu_blocking=(8, 16, 4), cpu_openmp=openmp, cpu_vectorize_info=vectorization).compile() without_blocking = ps.create_kernel(assignments).compile() print(f" openmp {openmp}, vectorization {vectorization}") dst_arr = np.zeros_like(src_arr) ref_arr = np.zeros_like(src_arr) np.copyto(src_arr, np.random.rand(*src_arr.shape)) with_blocking(src=src_arr, dst=dst_arr) without_blocking(src=src_arr, dst=ref_arr) np.testing.assert_almost_equal(ref_arr, dst_arr) def test_jacobi3d_var_size(): src, dst = ps.fields("src, dst: double[3D]", layout='c') print("Var Size: Smaller than block sizes") arr = np.empty([4, 5, 6]) check_equivalence(jacobi(dst, src), arr) print("Var Size: Large non divisible sizes") arr = np.empty([100, 80, 9]) check_equivalence(jacobi(dst, src), arr) print("Var Size: Multiples of block sizes") arr = np.empty([8*4, 16*2, 4*3]) check_equivalence(jacobi(dst, src), arr) def test_jacobi3d_fixed_size(): print("Fixed Size: Large non divisible sizes") arr = np.empty([10, 10, 9]) src, dst = ps.fields("src, dst: double[3D]", src=arr, dst=arr) check_equivalence(jacobi(dst, src), arr) print("Fixed Size: Smaller than block sizes") arr = np.empty([4, 5, 6]) src, dst = ps.fields("src, dst: double[3D]", src=arr, dst=arr) check_equivalence(jacobi(dst, src), arr) print("Fixed Size: Multiples of block sizes") arr = np.empty([8*4, 16*2, 4*3]) src, dst = ps.fields("src, dst: double[3D]", src=arr, dst=arr) check_equivalence(jacobi(dst, src), arr)