kerops 0.0.5

Efficient gpu algorithms for 3D computer vision

Kerops

Fast algorithms for GPU

Install

pip install kerops

How fast is it?

Time comparison (ms) for NVidia RTX 3090. Input is an array of size (1, channels, 350, 350, 128); float16; channels_last_3d. Compared to usual 3d convolution from torch (kernel_size=3, padding=1, stride=1, bias=False, in_channels=channels, out_channels=channels). Slowdown compared to copying is shown in parentheses.

channels	torch.clone	kerops.ops.DWConv	torch.nn.Conv3d(C->C)
8	0.61	0.79 (x1.30)	2.45 (x4.00)
16	1.21	1.41 (x1.17)	4.48 (x3.70)
32	2.40	2.99 (x1.25)	15.3 (x6.38)
64	4.78	6.29 (x1.32)	52.0 (x10.89)
128	9.55	12.8 (x1.34)	195.0 (x20.44)

channels	torch.clone	kerops.ops.DWConvWGRAD	torch.nn.Conv3d(C->C)
8	0.61	2.55 (x4.18)	7.14 (x11.70)
16	1.21	3.01 (x2.49)	12.1 (x10.00)
32	2.40	4.80 (x2.00)	24.6 (x10.25)
64	4.78	8.72 (x1.82)	71.3 (x14.91)
128	9.55	17.9 (x1.87)	245.0 (x25.65)