![]() So in the single mode we need to set affinity mask to ensure utilizing the fastest CPU core. From that point of view, multithreading can be useful (we use up to 12 threads), but in the single mode we could get different performance depending on the CPU core used. Since Tier-2 stage of JPEG2000 algorithm is implemented on CPU, the performance of both CPU and GPU cores determine the framerate. These two types of cores have different performance, which should be taken into account. Jetson TX2 has 4-core ARM Cortex-A57 2 GHz and 2-core Denver2 2 GHz. JPEG2000 codec benchmarks on NVIDIA Jetson TX2 It’s not the maximum performance, which could be better in many other cases. Our benchmarks show the performance results for the above images and parameters. Decreasing the quality coefficient one can get not only better compression, but also higher framerate both for encoding and decoding. So we would suggest testing different parameters to achieve the best compression ratio with an acceptable image quality. It’s obvious that in many cases compression ratio for visually lossless encoding could be much higher for JPEG2000 algorithm. Modes of operation – single or multithreaded batch.Progression order – LRCP (L = layer, R = resolution, C = component, P = position).Compression ratio (for lossy algorithm) ~ 12.0:1 which corresponds to visually lossless encoding.Lossless JPEG2000 compression with CDF 5/3 wavelet.Lossy JPEG2000 compression with CDF 9/7 wavelet.Here we follow exactly the same procedure, but it’s applied to the Jetson hardware. Since J2K compression is a common task for UAV (Unmanned Aerial Vehicle) applications, here we evaluate such a solution and its limitations.ĭetailed info concerning our testing approach for JPEG2000 encoding and decoding on desktop/server NVIDIA GPUs you can find at the corresponding links. That high-performance and low-power hardware is utilized in autonomous solutions, especially the industrial version Jetson TX2i. NVIDIA Jetson TX2 hardware is very promising for imaging and other embedded applications.
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