Performance & Benchmark

From CUVI Wiki

If one thing CUVI gives you, it's performance boost over competitive libraries and solutions. Using GPGPU as the underlying hardware, Imaging and Vision modules get maximum benefit due to their inherent parallel algorithms. In addition to cost cutting on CPU-based clusters, CUVI gives up to 15x speedup over Intel IPP.

Applications using CUVI are generally ten times faster than their CPU counterpart. CUVI framework also gives the ease to scale the application on more than one GPU making it as fast as you want.

Benchmark

The benchmark is performed on NVIDIA GTX 1080 via Nsight for Performance tool. The figure represents frames per second (fps) based on processing time on the GPU. The benchmark for demosaicDFPD (16-bit) for 1080p, 4k and 8k image is 1550 fps, 412 fps and 94 fps.

1080p Full HD 4k Ultra HD 8k Ultra HD
Auto Color 7088.83 fps 1850.02 fps 461.36 fps
Demosaic (DFPD) 1707.94 fps 412.72 fps 101.86 fps
Demosaic (Linear) 4258.88 fps 1025.64 fps 234.66 fps
Low Light Enhancement 2143.02 fps 525.16 fps 145.52 fps
Resize (2x - Nearest Neighbor) 4169.51 fps 1048.44 fps 260.164 fps
Resize (2x - Linear) 2494.80 fps 613.65 fps 151.53 fps
Resize (2x - Cubic) 1778.42 fps 456.68 fps 108.44 fps
Resize (0.5x - Nearest Neighbor) 47,265.68 fps 12,396.48 fps 3145.28 fps
Resize (0.5x - Linear) 26,365.05 fps 6793.71 fps 1703.32 fps
Resize (0.5x - Cubic) 11,232.92 fps 3143.94 fps 799.00 fps