Low GPU occupancy approach to fast arithmetic coding in JPEG2000
MEMICS'11 Proceedings of the 7th international conference on Mathematical and Engineering Methods in Computer Science
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The JPEG2000 image compression standard provides superior features to the popular JPEG standard; however, the slow performance of software implementation of JPEG2000 has kept it from being widely adopted. More than 80% of the execution time for JPEG2000 is spent on the Tier-1 coding engine. While much effort over the past decade has been devoted to optimizing this component, its performance still remains slow. The major reason for this is that the Tier-1 coder consists of highly serial operations, each operating on individual bits in every single bit plane of the image samples. In addition, in the past there lacked an efficient hardware platform to provide massively parallel acceleration for Tier-1. However, the recent growth of general purpose graphic processing unit (GPGPU) provides a great opportunity to solve the problem with thousands of parallel processing threads. In this paper, the computation steps in JPEG2000 are examined, particularly in the Tier-1, and novel, GPGPU compatible, parallel processing methods for the sample-level coding of the images are developed. The GPGPU-based parallel engine allows for significant speedup in execution time compared to the JasPer JPEG2000 compression software. Running on a single Nvidia GTX 480 GPU, the parallel wavelet engine achieves 100脳 speedup, the parallel bit plane coder achieves more than 30脳 speedup, and the overall Tier-1 coder achieves up to 17脳 speedup.