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Fix second implementation, add benchmark script

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* Third implementation is broken (WIP)
This commit is contained in:
Corentin 2021-06-25 02:49:28 +09:00
parent 6f04eb9db2
commit 7f4ec27235
6 changed files with 347 additions and 40 deletions
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97
examples/python_naive_matmul/matmul_plot.py Normal file
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from argparse import ArgumentParser
import cv2
import numpy as np
def plot_tensor(window_name: str, tensor: np.ndarray, coord_highlight: tuple[int, int] = None):
font_size = 48
image = np.zeros((tensor.shape[1] * font_size, tensor.shape[0] * font_size, 3), dtype=np.uint8)
for y in range(tensor.shape[1]):
for x in range(tensor.shape[0]):
if coord_highlight and x == coord_highlight[1] and y == coord_highlight[0]:
cv2.putText(
image, str(int(tensor[y, x])), (x * font_size, int((y + 0.8) * font_size)),
cv2.FONT_HERSHEY_TRIPLEX, 1., (127, 127, 255))
else:
cv2.putText(
image, str(int(tensor[y, x])), (x * font_size, int((y + 0.8) * font_size)),
cv2.FONT_HERSHEY_TRIPLEX, 1., (255, 255, 255))
cv2.imshow(window_name, image)
def main():
parser = ArgumentParser()
parser.add_argument('tensor_size', type=int, help='Size of the square tensors')
parser.add_argument('tile_size', type=int)
parser.add_argument('local_size', type=int, nargs=2)
parser.add_argument('workgroup', type=int, nargs=2)
arguments = parser.parse_args()
tensor_size: int = arguments.tensor_size
tile_size: int = arguments.tile_size
local_size: tuple[int, int, int] = tuple(arguments.local_size)
workgroup: tuple[int, int, int] = tuple(arguments.workgroup)
tensor_shape = (tensor_size, tensor_size)
tensor_1 = np.triu(np.ones(tensor_shape))
tensor_2 = np.triu(np.ones(tensor_shape))
tensor_out = np.zeros(tensor_shape)
tensor_test_1 = np.zeros(tensor_shape)
tensor_test_2 = np.zeros(tensor_shape)
tensor_test_3 = np.zeros(tensor_shape)
tensor_test_4 = np.zeros(tensor_shape)
tensor_test_5 = np.zeros(tensor_shape)
plot_tensor('tensor_1', tensor_1)
plot_tensor('tensor_2', tensor_2)
plot_tensor('tensor_out', tensor_out)
plot_tensor('tensor_test_1', tensor_test_1)
plot_tensor('tensor_test_2', tensor_test_2)
plot_tensor('tensor_test_3', tensor_test_3)
plot_tensor('tensor_test_4', tensor_test_4)
plot_tensor('tensor_test_5', tensor_test_5)
cv2.waitKey(-1)
print(f'{workgroup=} {local_size=}')
for workgroup_x in range(workgroup[0]):
for workgroup_y in range(workgroup[1]):
for invocation_x in range(workgroup_x * local_size[0], (workgroup_x + 1) * local_size[0]):
for invocation_y in range(workgroup_y * local_size[1], (workgroup_y + 1) * local_size[1]):
row = invocation_x
col = invocation_y
globalRow = (tile_size * workgroup_x) + row
globalCol = (tile_size * workgroup_y) + col
try:
tensor_out[row, col] = row
tensor_test_1[row, col] = col
tensor_test_2[row, col] = workgroup_x
tensor_test_3[row, col] = workgroup_y
tensor_test_4[row, col] = globalRow
tensor_test_5[row, col] = globalCol
plot_tensor('tensor_out', tensor_out, (row, col))
plot_tensor('tensor_test_1', tensor_test_1, (row, col))
plot_tensor('tensor_test_2', tensor_test_2, (row, col))
plot_tensor('tensor_test_3', tensor_test_3, (row, col))
plot_tensor('tensor_test_4', tensor_test_4, (row, col))
plot_tensor('tensor_test_5', tensor_test_5, (row, col))
cv2.waitKey(-1)
except IndexError as error:
print(f'{workgroup_x=} {workgroup_y=} {row=} {col=}')
raise error
plot_tensor('tensor_1', tensor_1)
plot_tensor('tensor_2', tensor_2)
plot_tensor('tensor_out', tensor_out)
plot_tensor('tensor_test_1', tensor_test_1)
plot_tensor('tensor_test_2', tensor_test_2)
plot_tensor('tensor_test_3', tensor_test_3)
plot_tensor('tensor_test_4', tensor_test_4)
plot_tensor('tensor_test_5', tensor_test_5)
cv2.waitKey(-1)
if __name__ == '__main__':
main()