CUDA ISP for NVIDIA Jetson/Performance/Library

CUDA ISP for NVIDIA Jetson
CUDA ISP for NVIDIA Jetson Basics
Getting Started
Evaluating the CUDA ISP Getting the code Building CUDA ISP for NVIDIA Jetson Building custom v4l2src element
User Manual
GStreamer
cudadebayer cudashift cudaawb
Examples
API usage GStreamer usage
Performance
Library GStreamer Elements
Contact Us

This page is still under development. Please, do not take the performance data as definitive.

Library API performance

To measure the CUDA ISP API performance, we built a simple example (provided upon request) that iterates over the Apply methods for each algorithm and records performance metrics for each iteration. We measured the duration of each algorithm's Apply method. We also measured CPU, CPU RAM, GPU, and GPU RAM usage for the complete processing pipeline iterating at 30fps. We ran the experiments on both 1080p and 4K buffers. We also ran the experiments on the Jetson Nano, Jetson Xavier NX, Jetson Xavier AGX, and Jetson AGX Orin.

• We measured the duration of each Apply method separately using the chrono library.
• We used the sys/times.h library to obtain the CPU usage.
• We read the /proc/self/status file to obtain the CPU RAM usage.
• We used jtop to measure GPU usage on the Jetson Nano and Jetson Xavier NX. We use jetson-stats to measure GPU usage on the Jetson Xavier AGX and the Jetson AGX Orin.
• We used cudaMemGetInfo from CUDA to measure GPU RAM usage.

This is the hardware setup we used:

• On the Jetson Nano, we used Jetpack 4.5.3 and MAXN Power Mode (NVP model 0)
• On the Jetson Xavier NX, we used Jetpack 4.5.3 and 20W 6 Core Power Mode (NVP model 8)
• On the Jetson Xavier AGX, we used Jetpack 4.5.1 and 30W 8 Core Power Mode (NVP model 3)
• On the Jetson AGX Orin, we used Jetpack 5.0.2 and MAXN Power Mode (NVP model 0)

The following table summarizes CUDA ISP's performance results. The values in parenthesis next to each processing time is the corresponding theoretical framerate calculated as the inverse of the time.

Algorithm	Jetson AGX Orin		Jetson Xavier AGX		Jetson Xavier NX		Jetson Nano
Buffer size	1080p	4K	1080p	4K	1080p	4K	1080p	4K
Duration (ms)
CudaShift	0.82	1.52					2104	7.52
CudaDebayer	0.68	1.30					2404	8.75
CudaWhiteBalancer (Gray World Algorithm)	0.84	1.66					2511	8.51
CudaWhiteBalancer (Histogram Stretch Algorithm)	1.24	1.91					3179	1.11
CudaColorSpaceConverter	0.91	1.60					2053	7.70
Framerate (fps)
CudaShift	1216	660					475	132
CudaDebayer	1479	771					415	114
CudaWhiteBalancer (Gray World Algorithm)	1197	603					398	117
CudaWhiteBalancer (Histogram Stretch Algorithm)	807	522					314	90
CudaColorSpaceConverter	1104	623					487	129
CPU usage (%)
CudaShift	0.198	0.218					0.800	0.817
CudaDebayer	0.121	0.161					0.873	0.665
CudaWhiteBalancer (Gray World Algorithm)	0.201	0.277					1.286	1.299
CudaWhiteBalancer (Histogram Stretch Algorithm)	0.260	0.280					1.569	1.454
CudaColorSpaceConverter	0.172	0.201					0.647	0.680
CPU RAM (MB)
CudaShift	89.7	90.8					77.5	88.7
CudaDebayer	44.4	44.5					33.0	33.4
CudaWhiteBalancer (Gray World Algorithm)	99.8	99.1					40.6	77.5
CudaWhiteBalancer (Histogram Stretch Algorithm)	99.2	99.3					52.1	33.0
CudaColorSpaceConverter	44.1	44.3					33.2	89.1
GPU usage (%)
CudaShift	12.29	7.81					85.32	25.96
CudaDebayer	11.6	13.04					67.27	42.53
CudaWhiteBalancer (Gray World Algorithm)	9.75	19.27					20.24	75.14
CudaWhiteBalancer (Histogram Stretch Algorithm)	8.89	24.42					26.84	83.35
CudaColorSpaceConverter	4.85	9.14					20.11	81.19
GPU RAM (MB)
CudaShift	26.8	28.4					41.6	43.3
CudaDebayer	6.0	6.1					11.9	11.8
CudaWhiteBalancer (Gray World Algorithm)	33.7	32.7					40.6	31.5
CudaWhiteBalancer (Histogram Stretch Algorithm)	33.2	33.4					52.1	52.4
CudaColorSpaceConverter	5.4	6.0					11.2	11.8