def _test(sdfg):
# 4D kernel with 5D block
N = 12
M = 3
K = 14
L = 15
X = 1
Y = 2
Z = 3
W = 4
U = 5
dims = tuple(s for s in (N, M, K, L, X, Y, Z, W, U))
outdims = tuple(s for s in (N, M, K, L))
print('High-dimensional GPU kernel test', dims)
A = dace.ndarray((N, M, K, L, X, Y, Z, W, U), dtype=dace.uint64)
B = dace.ndarray((N, M, K, L), dtype=dace.uint64)
A[:] = np.random.randint(10, size=dims).astype(np.uint64)
B[:] = np.zeros(outdims, dtype=np.uint64)
B_regression = np.zeros(outdims, dtype=np.uint64)
# Equivalent python code
for i, j, k, l in dace.ndrange(makendrange(5, N - 5, 0, M, 7, K - 1, 0,
L)):
for a, b, c, d, e in dace.ndrange(
makendrange(0, X, 0, Y, 1, Z, 2, W - 2, 0, U)):
B_regression[i, j, k, l] += A[i, j, k, l, a, b, c, d, e]
sdfg(A=A, B=B, N=N, M=M, K=K, L=L, X=X, Y=Y, Z=Z, W=W, U=U)
diff = np.linalg.norm(B_regression - B) / (N * M * K * L)
print('Difference:', diff)
assert diff <= 1e-5
Y.set(2)
Z.set(3)
W.set(4)
U.set(5)
dims = tuple(s.get() for s in (N, M, K, L, X, Y, Z, W, U))
outdims = tuple(s.get() for s in (N, M, K, L))
print('High-dimensional GPU kernel test', dims)
A = dace.ndarray((N, M, K, L, X, Y, Z, W, U), dtype=dace.uint64)
B = dace.ndarray((N, M, K, L), dtype=dace.uint64)
A[:] = np.random.randint(10, size=dims).astype(np.uint64)
B[:] = np.zeros(outdims, dtype=np.uint64)
B_regression = np.zeros(outdims, dtype=np.uint64)
# Equivalent python code
for i, j, k, l in dace.ndrange(
makendrange(5,
N.get() - 5, 0, M.get(), 7,
K.get() - 1, 0, L.get())):
for a, b, c, d, e in dace.ndrange(
makendrange(0, X.get(), 0, Y.get(), 1, Z.get(), 2,
W.get() - 2, 0, U.get())):
B_regression[i, j, k, l] += A[i, j, k, l, a, b, c, d, e]
highdim(A, B)
diff = np.linalg.norm(B_regression - B) / (N.get() * M.get() * K.get() *
L.get())
print('Difference:', diff)
exit(0 if diff <= 1e-5 else 1)
# 4D kernel with 5D block
N.set(12)
M.set(3)
K.set(14)
L.set(15)
X.set(1)
Y.set(2)
Z.set(3)
W.set(4)
U.set(5)
dims = tuple(s.get() for s in (N, M, K, L, X, Y, Z, W, U))
outdims = tuple(s.get() for s in (N, M, K, L))
print('High-dimensional GPU kernel test', dims)
A = np.random.randint(10, size=dims).astype(np.uint64)
B = np.zeros(outdims, dtype=np.uint64)
B_regression = np.zeros(outdims, dtype=np.uint64)
# Equivalent python code
for i, j, k, l in dace.ndrange(
makendrange(5, N - 5, 0, M, 7, K - 1, 0, L)):
for a, b, c, d, e in dace.ndrange(
makendrange(0, X, 0, Y, 1, Z, 2, W - 2, 0, U)):
B_regression[i, j, k, l] += A[i, j, k, l, a, b, c, d, e]
highdim(A, B)
diff = np.linalg.norm(B_regression - B) / dace.eval(N * M * K * L)
print('Difference:', diff)
exit(0 if diff <= 1e-5 else 1)