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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)