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FZ-GPU: A Fast and High-Ratio Lossy Compressor for Scientific Computing Applications on GPUs
Article describes how today's large-scale scientific applications running on high-performance computing (HPC) systems generate vast data volumes. Thus, data compression is becoming a critical technique to mitigate the storage burden and data-movement cost. In this paper, the authors develop a fast and high- ratio error-bounded lossy compressor on GPUs for scientific data (called FZ-GPU).
Date:
August 7, 2023
Creator:
Zhang, Bouyan; Tian, Jiannan; Di, Sheng; Yu, Xiaodong; Feng, Yunhe; Liang, Xin et al.
System:
The UNT Digital Library