TY - CHAP
T1 - Exploring Level-Wise Interpolation to Improve Lossy Compression Ratio for AMR Applications
AU - Li, Yida
AU - Luo, Huizhang
AU - Liu, Chubo
AU - Li, Kenli
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - Adaptive Mesh Refinement (AMR) is widely adopted in High-Performance Computing (HPC) systems. However, none of existing AMR storage solutions has considered the high similarities among the adjacent AMR levels, which leads to a lower storage efficiency. In this paper, we propose level-wise data interpolation techniques to further reduce the storage of AMR applications. In particular, it generates finer level data based on coarser levels. Then, the differences (deltas) between the interpolated data and original data are stored to achieve a higher compression ratio for lossy compressors. We firstly use median absolute deviation and standard deviation to decide which interpolations are adopted. After that, we evaluate the effectiveness of level-wise interpolation with ZFP and SZ lossy compressors. The experimental results show that the compression ratio of deltas are improved up to 3 × compared to directly compressing the finer level data.
AB - Adaptive Mesh Refinement (AMR) is widely adopted in High-Performance Computing (HPC) systems. However, none of existing AMR storage solutions has considered the high similarities among the adjacent AMR levels, which leads to a lower storage efficiency. In this paper, we propose level-wise data interpolation techniques to further reduce the storage of AMR applications. In particular, it generates finer level data based on coarser levels. Then, the differences (deltas) between the interpolated data and original data are stored to achieve a higher compression ratio for lossy compressors. We firstly use median absolute deviation and standard deviation to decide which interpolations are adopted. After that, we evaluate the effectiveness of level-wise interpolation with ZFP and SZ lossy compressors. The experimental results show that the compression ratio of deltas are improved up to 3 × compared to directly compressing the finer level data.
KW - Adaptive mesh refinement
KW - Data reduction
KW - High-performance computing
KW - Level-wise interpolation
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U2 - 10.1007/978-3-030-89698-0_27
DO - 10.1007/978-3-030-89698-0_27
M3 - Chapter
AN - SCOPUS:85122337215
T3 - Lecture Notes on Data Engineering and Communications Technologies
SP - 259
EP - 266
BT - Lecture Notes on Data Engineering and Communications Technologies
PB - Springer Science and Business Media Deutschland GmbH
ER -