120 lines
3.1 KiB
Python
120 lines
3.1 KiB
Python
import numpy as np
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from numba import cuda, float64, void
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from numba.cuda.testing import unittest, CUDATestCase
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from numba.core import config
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# NOTE: CUDA kernel does not return any value
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if config.ENABLE_CUDASIM:
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tpb = 4
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else:
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tpb = 16
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SM_SIZE = tpb, tpb
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class TestCudaLaplace(CUDATestCase):
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def test_laplace_small(self):
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@cuda.jit(float64(float64, float64), device=True, inline=True)
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def get_max(a, b):
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if a > b:
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return a
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else:
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return b
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@cuda.jit(void(float64[:, :], float64[:, :], float64[:, :]))
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def jocabi_relax_core(A, Anew, error):
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err_sm = cuda.shared.array(SM_SIZE, dtype=float64)
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ty = cuda.threadIdx.x
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tx = cuda.threadIdx.y
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bx = cuda.blockIdx.x
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by = cuda.blockIdx.y
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n = A.shape[0]
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m = A.shape[1]
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i, j = cuda.grid(2)
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err_sm[ty, tx] = 0
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if j >= 1 and j < n - 1 and i >= 1 and i < m - 1:
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Anew[j, i] = 0.25 * ( A[j, i + 1] + A[j, i - 1]
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+ A[j - 1, i] + A[j + 1, i])
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err_sm[ty, tx] = Anew[j, i] - A[j, i]
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cuda.syncthreads()
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# max-reduce err_sm vertically
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t = tpb // 2
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while t > 0:
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if ty < t:
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err_sm[ty, tx] = get_max(err_sm[ty, tx], err_sm[ty + t, tx])
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t //= 2
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cuda.syncthreads()
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# max-reduce err_sm horizontally
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t = tpb // 2
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while t > 0:
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if tx < t and ty == 0:
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err_sm[ty, tx] = get_max(err_sm[ty, tx], err_sm[ty, tx + t])
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t //= 2
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cuda.syncthreads()
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if tx == 0 and ty == 0:
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error[by, bx] = err_sm[0, 0]
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if config.ENABLE_CUDASIM:
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NN, NM = 4, 4
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iter_max = 20
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else:
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NN, NM = 256, 256
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iter_max = 1000
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A = np.zeros((NN, NM), dtype=np.float64)
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Anew = np.zeros((NN, NM), dtype=np.float64)
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n = NN
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tol = 1.0e-6
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error = 1.0
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for j in range(n):
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A[j, 0] = 1.0
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Anew[j, 0] = 1.0
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iter = 0
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blockdim = (tpb, tpb)
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griddim = (NN // blockdim[0], NM // blockdim[1])
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error_grid = np.zeros(griddim)
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stream = cuda.stream()
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dA = cuda.to_device(A, stream) # to device and don't come back
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dAnew = cuda.to_device(Anew, stream) # to device and don't come back
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derror_grid = cuda.to_device(error_grid, stream)
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while error > tol and iter < iter_max:
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self.assertTrue(error_grid.dtype == np.float64)
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jocabi_relax_core[griddim, blockdim, stream](dA, dAnew, derror_grid)
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derror_grid.copy_to_host(error_grid, stream=stream)
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# error_grid is available on host
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stream.synchronize()
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error = np.abs(error_grid).max()
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# swap dA and dAnew
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tmp = dA
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dA = dAnew
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dAnew = tmp
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iter += 1
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if __name__ == '__main__':
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unittest.main()
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