from __future__ import print_function, absolute_import, division
import numpy as np
import time
from numba import cuda, float64, void
from numba.cuda.testing import unittest

# NOTE: CUDA kernel does not return any value

tpb = 16
SM_SIZE = tpb, tpb


@cuda.jit(float64(float64, float64), device=True, inline=True)
def get_max(a, b):
    if a > b:
        return a
    else:
        return b


@cuda.jit(void(float64[:, :], float64[:, :], float64[:, :]))
def jocabi_relax_core(A, Anew, error):
    err_sm = cuda.shared.array(SM_SIZE, dtype=float64)

    ty = cuda.threadIdx.x
    tx = cuda.threadIdx.y
    bx = cuda.blockIdx.x
    by = cuda.blockIdx.y

    n = A.shape[0]
    m = A.shape[1]

    i, j = cuda.grid(2)

    err_sm[ty, tx] = 0
    if j >= 1 and j < n - 1 and i >= 1 and i < m - 1:
        Anew[j, i] = 0.25 * ( A[j, i + 1] + A[j, i - 1] \
                              + A[j - 1, i] + A[j + 1, i])
        err_sm[ty, tx] = Anew[j, i] - A[j, i]

    cuda.syncthreads()

    # max-reduce err_sm vertically
    t = tpb // 2
    while t > 0:
        if ty < t:
            err_sm[ty, tx] = get_max(err_sm[ty, tx], err_sm[ty + t, tx])
        t //= 2
        cuda.syncthreads()

    # max-reduce err_sm horizontally
    t = tpb // 2
    while t > 0:
        if tx < t and ty == 0:
            err_sm[ty, tx] = get_max(err_sm[ty, tx], err_sm[ty, tx + t])
        t //= 2
        cuda.syncthreads()

    if tx == 0 and ty == 0:
        error[by, bx] = err_sm[0, 0]


class TestCudaLaplace(unittest.TestCase):
    def test_laplace_small(self):
        NN = 256
        NM = 256

        A = np.zeros((NN, NM), dtype=np.float64)
        Anew = np.zeros((NN, NM), dtype=np.float64)

        n = NN
        m = NM
        iter_max = 1000

        tol = 1.0e-6
        error = 1.0

        for j in range(n):
            A[j, 0] = 1.0
            Anew[j, 0] = 1.0

        timer = time.time()
        iter = 0

        blockdim = (tpb, tpb)
        griddim = (NN // blockdim[0], NM // blockdim[1])

        error_grid = np.zeros(griddim)

        stream = cuda.stream()

        dA = cuda.to_device(A, stream)          # to device and don't come back
        dAnew = cuda.to_device(Anew, stream)    # to device and don't come back
        derror_grid = cuda.to_device(error_grid, stream)

        while error > tol and iter < iter_max:
            self.assertTrue(error_grid.dtype == np.float64)

            jocabi_relax_core[griddim, blockdim, stream](dA, dAnew, derror_grid)

            derror_grid.copy_to_host(error_grid, stream=stream)


            # error_grid is available on host
            stream.synchronize()

            error = np.abs(error_grid).max()

            # swap dA and dAnew
            tmp = dA
            dA = dAnew
            dAnew = tmp

            iter += 1

        runtime = time.time() - timer


if __name__ == '__main__':
    unittest.main()
