Benchmarks for J2K decoders on CPU and GPU

Below we provide the benchmarks for Fastvideo JPEG2000 Decoder on NVIDIA GPU in comparison with other freely available open source and proprietary J2K decoding software on CPU.

Approaches for J2K decoder performance measurements

There are two standard approaches to performance measurements of JPEG2000 codecs, which utilize GPU. They correspond to the two most common use cases for J2K decoders.

1. Single image mode consists in processing of single image at a time and could be called "latency-oriented" or "low latency" approach. In that case the time interval (latency) between availability of original image in RAM and availability of the processed image in RAM is measured. It means that software cannot expect that any additional images will be processed at the same time and therefore cannot take advantage of multiple image decoding. Overlapping of current image processing with other activities is undesirable because it would increase total latency.

2. Batch mode consists in processing of batch of images and could be called "throughput-oriented" or "maximum performance". In that case frame rate becomes more important than latency. It is calculated via division of the total time of processing by the number of processed images. Some J2K decoders are optimized for this use case, meaning that exploiting of task parallelism leads to better frame rate (throughput) at the expense of increased processing time for separate images. It is possible, because we actually have three devices (CPU, GPU and bus interface between them), which can be used simultaneously in that mode, whereas at single image mode these devices are used sequentially for different stages of JPEG2000 algorithm. Moreover, GPU can process several images simultaneously to increase frame rate even more, if each image is too small for decoder to load a multitude of GPU cores (especially at Tier-1 stage). Important limitation for simultaneous processing of several images is imposed by amount of free GPU memory. Batch mode is a must for streaming applications when the pipeline contains J2K decoder. For more complicated workflow it could be better to utilize single image mode, though fps will be reduced.

j2k decoder benchmarks

Briefly, J2K decoder at batch mode can take into account specific methods of task parallelism, based on the following:

  • both upload to GPU and download from GPU could overlap with JPEG2000 processing on GPU (CUDA Streams)
  • Tier-1 and Tier-2 could be done in parallel: Tier-1 on GPU and multithreaded Tier-2 on CPU at the same time
  • multiple (batch) J2K processing to increase general GPU occupancy

CPU-based JPEG2000 solutions have no explicit implementation of batch mode, because all processing stages are done on CPU and complete loading of available CPU cores can be achieved by simply running multiple decoders in separate processes. Multithreaded mode of CPU-based J2K decoders decreases latency of single image processing, so we can consider this mode as single image mode.

At the moment we don't consider here the following possible modes for J2K decoding on GPU:

  • multiple GPU mode
  • multiple tile mode for big images
  • fast parallel J2K processing with RESET, RESTART, CAUSAL and BYPASS modes

Results for all these modes will be published as soon as their implementations are ready.

We don't hide anything concerning benchmarking procedures and the achieved results. Thus, everyone can always reproduce our benchmarks, because we publish not only timing and performance, we supply full info about hardware, JPEG2000 parameters, test images and testing modes.

J2K decoding benchmarks

We've carried out time and performance measurements for JPEG2000 decoding for 24-bit images with 2K and 4K resolutions. All results don't include any host I/O latency (image loading to RAM from HDD/SSD and saving back) and we've also excluded host-to-device transfer time. We've done such an assumption to reproduce J2K decoder usage in our conventional image processing pipeline, when decompressed data reside in GPU memory. Results for GPU-based JPEG2000 decoding software also include Tier-2 time on CPU, because this stage in our implementation is performed on CPU. In the tables below, one can find averaged results for the best series of 100 measurements.

JPEG2000 decoderJPEG2000 decoding parameters

  • File format – JP2
  • Lossy JPEG 2000 with CDF 9/7 wavelet
  • Lossless JPEG 2000 with CDF 5/3 wavelet
  • Compression ratio (for lossy algorithm) ~ 12.0 which corresponds to visually lossless compression
  • Subsampling mode – 4:4:4
  • Number of DWT resolutions – 7
  • Codeblock size – 32×32
  • MCT – on
  • PCRD – off
  • Tiling – off
  • Quality layers – one
  • Progression order – LRCP (L = layer, R = resolution, C = component, P = position)
  • Modes of operation – single or batch

Test images

Hardware and software

  • CPU Intel Core i9-9960X
  • GPU NVIDIA GeForce RTX 2080TI
  • OS Windows 10 (x64), version 1803
  • CUDA Toolkit 10.2

JPEG2000 Decoders for comparison

  • OpenJPEG 2.3.1
  • Jasper 2.0.16
  • J2K-Codec 2.2
  • Kakadu 7.10.2
  • Fastvideo JPEG2000 (SDK version 0.16.1.6)

J2K decoding at single image mode for 2K image with lossy compression: 2k_wild_lossy.jp2 (1920×1080, 4:4:4, 24-bit)

JPEG2000 decoders Average decoding time Performance Frames per second Hardware
OpenJPEG (single thread) 162 ms 36.6 MB/s 6.2 fps CPU
OpenJPEG (16 threads) 65 ms 91.3 MB/s 15.4 fps CPU
Jasper 385 ms 15.4 MB/s 2.6 fps CPU
J2K-Codec 110 ms 53.9 MB/s 9.1 fps CPU
Kakadu (single thread) 84 ms 70.6 MB/s 11.9 fps CPU
Kakadu (16 threads) 19 ms 312 MB/s 52.6 fps CPU
Fastvideo JPEG2000 decoder 10.1 ms 585 MB/s 98.6 fps GPU + CPU

J2K decoding at single image mode for 4K image with lossy compression: 4k_wild_lossy.jp2 (3840×2160, 4:4:4, 24-bit)

JPEG2000 decoders Average decoding time Performance Frames per second Hardware
OpenJPEG (single thread) 701 ms 33.9 MB/s 1.4 fps CPU
OpenJPEG (16 threads) 315 ms 75.3 MB/s 3.2 fps CPU
Jasper 1478 ms 16.1 MB/s 0.7 fps CPU
J2K-Codec 469 ms 50.6 MB/s 2.1 fps CPU
Kakadu (single thread) 372 ms 63.8 MB/s 2.7 fps CPU
Kakadu (16 threads) 71 ms 334 MB/s 14.1 fps CPU
Fastvideo JPEG2000 decoder 23.9 ms 993 MB/s 41.8 fps GPU + CPU

MB/s – MegaBytes per second

J2K decoding at single image mode for 2K image with lossless compression: 2k_wild_lossless.jp2 (1920×1080, 4:4:4, 24-bit)

JPEG2000 decoders Average decoding time Performance Frames per second Hardware
OpenJPEG (single thread) 574 ms 10.3 MB/s 1.7 fps CPU
OpenJPEG (16 threads) 61 ms 97.3 MB/s 16.4 fps CPU
Jasper 820 ms 7.2 MB/s 1.2 fps CPU
J2K-Codec 390 ms 15.2 MB/s 2.6 fps CPU
Kakadu (single thread) 500 ms 11.9 MB/s 2.0 fps CPU
Kakadu (16 threads) 47 ms 126.2 MB/s 21.3 fps CPU
Fastvideo JPEG2000 decoder 15.1 ms 393 MB/s 66.2 fps GPU + CPU

J2K decoding at single image mode for 4K image with lossless compression: 4k_wild_lossless.jp2 (3840×2160, 4:4:4, 24-bit)

JPEG2000 decoders Average decoding time Performance Frames per second Hardware
OpenJPEG (single thread) 1821 ms 13.0 MB/s 0.5 fps CPU
OpenJPEG (16 threads) 196 ms 121.1 MB/s 5.1 fps CPU
Jasper 3141 ms 7.6 MB/s 0.3 fps CPU
J2K-Codec 1312 ms 18.1 MB/s 0.8 fps CPU
Kakadu (single thread) 1562 ms 15.2 MB/s 0.6 fps CPU
Kakadu (16 threads) 139 ms 170.7 MB/s 7.2 fps CPU
Fastvideo JPEG2000 decoder 35.6 ms 667 MB/s 28.1 fps GPU + CPU

MB/s – MegaBytes per second

Superior performance of JPEG 2000 decoding at batch mode

For batch mode we've carried out performance measurements for JPEG 2000 decoding exactly with the same parameters as we used at single image mode. In the table below, you can find averaged results for the best series of measurements (each lasting 10 seconds). All results don't include host I/O latency (image loading to RAM from HDD/SSD and saving back).

To get maximum performance at batch mode, we don't need very large images as for single image mode. For example, 4K image contains 4 times more pixels compared to 2K. It means that at batch mode we can expect that decoding time for 2K will be 4 times less than for 4K. In theory, if at single image mode we can do JPEG2000 decoding for 2K at 98 fps and for 4K at 42 fps, then it could be possible to achieve frame rate 42*4=168 fps for 2K decoding speed by processing 4 images with 2K resolution simultaneously, as a batch. We could expect even higher speedup using greater batch size, since at single image mode GPU is not completely occupied with 4K images and batch size for 2K is more than 4. If we also take into account simultaneous processing on both CPU and GPU, which is possible at batch mode, one could get additional acceleration for J2K decoding.

JPEG2000 decoding benchmarks at the multithreaded batch mode

  2k_wild_lossy.jp2 4k_wild_lossy.jp2 2k_wild_lossless.jp2 4k_wild_lossless.jp2 8k_wild_lossy.jp2
Fastvideo J2K decoder 461 fps 113 fps 136 fps 43.9 fps 31.8 fps
Kakadu 7.10.2 (16 threads) 52.6 fps 14.1 fps 21.3 fps 7.2 fps 4.2 fps
OpenJPEG 2.3.1 (16 threads) 15.4 fps 3.2 fps 16.4 fps 5.1 fps --
OpenJPEG 2.3.1 (1 thread) 6.2 fps 1.4 fps 1.7 fps 0.5 fps --
J2K-Codec 2.2 9.1 fps 2.1 fps 2.6 fps 0.8 fps 0.5 fps

We have published all info concerning time measurements, together with sample images, JPEG2000 parameters and hardware specifications to offer everyone an opportunity to reproduce our results and to check performance measurements for other J2K decoders at the same testing conditions. Our demo for fast JPEG2000 codec for Windows could be downloaded here.

JPEG2000 decoder benchmarks on the NVIDIA GeForce RTX 4090 at the multithreaded batch mode

JPEG2000 decoding parameters Lossy decoding Lossless decoding
2K image, 2k_wild_lossy.jp2 / 2k_wild_lossless.jp2 1350 fps 550 fps
4K image, 4k_wild_lossy.jp2 / 4k_wild_lossless.jp2 325 fps 168 fps

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