cupy_example.py

# Notes for https://numba.discourse.group/t/kernel-within-a-kernel/1582/4

import cupy as cp


def where(d2_array, col_index, _data_):
    return d2_array[cp.where(d2_array[:, col_index] == _data_)]


def fill_arrays_with_data_based_on_unique_data(unique_data, cp_data,
                                               cuda_array_of_arrays, col_index,
                                               book_size, long_book):
    """
    :param unique_data: unique data is a one dimentional array
    :param cp_data: is a huge 2D Array
    :param cuda_array_of_arrays: empty array of 2D arrays where data will be
                                 filtered by member of the unique_data
    :param col_index: index of the column
    :param book_size: book size (int)
    :param long_book: is 1 or 0; True/False
    :return: cuda_array_of_arrays array of 2D arrays filtered by date
             unique_data

    """

    for _index in range(unique_data.shape[0]):
        arr = cuda_array_of_arrays[_index]
        _data_ = unique_data[_index]
        counter = 0
        rank = book_size
        # would be lovely if below (where) function worked, but it doesn't
        cp_2d_array = where(cp_data, col_index, _data_)
        # would be great if below for loop could execute in parallel using
        # seperate kernel function
        for row in range(cp_2d_array.shape[0]):
            if counter < arr.shape[0]:
                for col in range(cp_2d_array.shape[1]):
                    arr[counter, col] = cp_2d_array[row, col]
                if long_book == 1:
                    # would be very usefuls if np.argsort() worked in numba
                    # cuda
                    arr[counter, 3] = rank
                    arr[counter, 10] = arr[counter, 7]
                    arr[counter, 13] = arr[counter, 8]
                    rank -= 1
                counter += 1


unique_data = cp.zeros(10)
cp_data = cp.zeros((100, 100))
cuda_array_of_arrays = [cp.zeros((100, 100)) for _ in range(10)]
col_index = 2
book_size = 5
long_book = 1

fill_arrays_with_data_based_on_unique_data(unique_data, cp_data,
                                           cuda_array_of_arrays, col_index,
                                           book_size, long_book)