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 GTX 1080.
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 |