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PyAPI: Speed up Mesh.shade_flat() using foreach_set #114591

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Thomas Barlow wants to merge 1 commits from Mysteryem/blender:speed_up_mesh_shade_flat into main
pull from: Mysteryem/blender:speed_up_mesh_shade_flat
merge into: blender:main

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Thomas Barlow commented 2023-11-07 18:31:31 +01:00
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Replace the slower iteration in Python with using foreach_set and a
compatible buffer object filled with True.

For meshes under 24 faces, the new code is slightly slower due to higher
overhead, but the increase in performance as the number of faces
increases should more than make up for this.

NumPy is only used to create a buffer filled with True that is
compatible with foreach_set. The array module does not support the
bool/'?' type, and ctypes arrays are not currently considered
compatible buffers by foreach_set.

No changes, other than performance, are expected with this patch.

Time per call for me for meshes with:

  • 24 faces:
    • Before: ~0.0053ms
    • After: ~0.0042ms
    • ~1.3 times faster
  • 1536 faces:
    • Before: ~0.24ms
    • After: ~0.0044ms
    • ~52 times faster
  • 24576 faces:
    • Before: ~3.79ms
    • After: ~0.0053ms
    • ~719 times faster
  • 393216 faces:
    • Before: ~58.5ms
    • After: ~0.018ms
    • ~3327 times faster

ctypes arrays use byte-order/size/alignment prefixes which foreach_set doesn't support, which would fall back to foreach_set's slower iteration.

For comparison, using a Python list with foreach_get is also many times faster and has less overhead, but is not as fast when the number of faces increases:
Time per call using sharp_faces_data.foreach_set("value", [True] * len(sharp_faces_data)):

  • 24 faces:
    • ~0.0023ms
    • ~2.3 times faster
  • 1536 faces:
    • ~0.018ms
    • ~13.3 times faster
  • 24576 faces:
    • ~0.25ms
    • ~15.2 times faster
  • 393216 faces:
    • ~3.97ms
    • ~14.7 times faster

Graph of speedup for meshes starting at 6 faces and doubling each time up to 1,572,864 faces:
image

Replace the slower iteration in Python with using `foreach_set` and a compatible buffer object filled with `True`. For meshes under 24 faces, the new code is slightly slower due to higher overhead, but the increase in performance as the number of faces increases should more than make up for this. NumPy is only used to create a buffer filled with `True` that is compatible with `foreach_set`. The `array` module does not support the `bool`/`'?'` type, and ctypes arrays are not currently considered compatible buffers by `foreach_set`. No changes, other than performance, are expected with this patch. Time per call for me for meshes with: - 24 faces: - Before: ~0.0053ms - After: ~0.0042ms - ~1.3 times faster - 1536 faces: - Before: ~0.24ms - After: ~0.0044ms - ~52 times faster - 24576 faces: - Before: ~3.79ms - After: ~0.0053ms - ~719 times faster - 393216 faces: - Before: ~58.5ms - After: ~0.018ms - ~3327 times faster --- ctypes arrays use byte-order/size/alignment prefixes which `foreach_set` doesn't support, which would fall back to `foreach_set`'s slower iteration. --- For comparison, using a Python list with `foreach_get` is also many times faster and has less overhead, but is not as fast when the number of faces increases: Time per call using `sharp_faces_data.foreach_set("value", [True] * len(sharp_faces_data))`: - 24 faces: - ~0.0023ms - ~2.3 times faster - 1536 faces: - ~0.018ms - ~13.3 times faster - 24576 faces: - ~0.25ms - ~15.2 times faster - 393216 faces: - ~3.97ms - ~14.7 times faster --- Graph of speedup for meshes starting at 6 faces and doubling each time up to 1,572,864 faces: ![image](/attachments/d6aeedc9-f274-401b-9744-d6e9bea0b79d)
image.png
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Iliya Katushenock added the
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 labels 2023-11-07 18:45:40 +01:00
Thomas Barlow force-pushed speed_up_mesh_shade_flat from 0af98fa117 to b109c5f668 2024-01-27 02:56:39 +01:00 Compare
Thomas Barlow commented 2024-01-27 02:59:32 +01:00
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I've updated the performance comparison following recent performance improvements to foreach_set, and I've rebased on main.

I've updated the performance comparison following recent performance improvements to `foreach_set`, and I've rebased on main.
Thomas Barlow commented 2024-01-30 18:58:56 +01:00
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An alternative that uses struct.pack rather than numpy could be:

import struct
sharp_faces_data = _name_convention_attribute_ensure(self.attributes, "sharp_face", 'FACE', 'BOOLEAN').data
true_buffer = memoryview(struct.pack("?", True) * len(sharp_faces_data)).cast("?")
sharp_faces_data.foreach_set("value", true_buffer)

This is also slightly faster than using numpy, but it doesn't amount to much when the code was already so fast. Notably though, it does have lower overhead, so is faster than the original code for even meshes as small as a default cube.

An alternative that uses `struct.pack` rather than `numpy` could be: ```py import struct sharp_faces_data = _name_convention_attribute_ensure(self.attributes, "sharp_face", 'FACE', 'BOOLEAN').data true_buffer = memoryview(struct.pack("?", True) * len(sharp_faces_data)).cast("?") sharp_faces_data.foreach_set("value", true_buffer) ``` This is also slightly faster than using `numpy`, but it doesn't amount to much when the code was already so fast. Notably though, it does have lower overhead, so is faster than the original code for even meshes as small as a default cube.
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