Cache-aware volume rendering methods with dynamic data reorganization


 We present two cache-aware methods for accelerating volume rendering on graphics processing units (GPUs). The proposed methods extend a previous method such that they improve the worst frame rate typically observed at oblique viewing angles. The key technique for realizing this extension is a dynamic reorganization of the volume data that improves the data locality based on the expected data access pattern. The proposed methods are: (1) a basic method which requires three times the amount of memory to store the volume and (2) an adaptive method which utilizes on-the-fly data reorganization to achieve similar performance without increasing the memory consumption. Experimental results indicate that the GPU texture cache hit rate increased from 58.8 to 71.8% for oblique viewing angles using a 1 GB data set, compared to the previous method. Furthermore, the maximum speedup of the proposed adaptive method was 3.6\(\times\) that of the previous method.

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This study was supported in part by the Japan Society for the Promotion of Science KAKENHI Grant Numbers 15H01687 and 16H02801, and “Program for Leading Graduate Schools” of the Ministry of Education, Culture, Sports, Science, and Technology, Japan. We are also grateful to the anonymous reviewers for their valuable comments.

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Correspondence to Ruiyun Zhu.

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Zhu, R., Misaki, Y., Walldén, M. et al. Cache-aware volume rendering methods with dynamic data reorganization. J Vis (2021).

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  • Cache optimization
  • Visualization
  • Data reorganization