'Test issue of warp misalign address due to nvvm not knowing the
alignment(? but it should have taken the natural alignment of the type)'

def test_issue_2393(self):

    num_weights = 2
    num_blocks = 48
    examples_per_block = 4
    threads_per_block = 1
    @cuda.jit
    def costs_func(d_block_costs):
        s_features = cuda.shared.array((examples_per_block, num_weights), float64)
        s_initialcost = cuda.shared.array(7, float64)
        threadIdx = cuda.threadIdx.x
        prediction = 0
        for j in range(num_weights):
            prediction += s_features[(threadIdx, j)]
        d_block_costs[0] = (s_initialcost[0] + prediction)
    block_costs = np.zeros(num_blocks, dtype=np.float64)
    d_block_costs = cuda.to_device(block_costs)
    costs_func[(num_blocks, threads_per_block)](d_block_costs)
    cuda.synchronize()
