Presentation

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GPU Compression (for Scientific Data) Done Right

SessionResearch, ACM SRC, and Doctoral Showcase Posters

DescriptionError-bounded lossy compression is a critical technique for significantly reducing scientific data volumes. Compared to CPU-based compressors, GPU-based compressors exhibit substantially higher throughputs, fitting better for today's HPC applications. To overcome the data challenge, GPU-based scientific lossy compressors have been created. Notably, cuSZ has been proposed as the error-bounded compression framework and has become the design base of the subsequent work. A plethora of derived work has been proposed, leading to the discussion of optimality considering data quality, compression ratio, and data processing speed. This paper covers new research directions: the compressibility study, the new encoding study, and the applicability study.

Authors

Jiannan Tian

Indiana University

Xin Liang

University of Kentucky