Performance & Benchmark
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 |