What to Support When You're Compressing: The State of Practice Gaps and Opportunities for Scientific Data Compression
Franck Cappello, Robert Underwood, Yuri Alexeev, Allison H. Baker, Ebru Bozdag, Martin Burtscher, Kyle Chard, Sheng Di, Kyle Gerard Felker, Paul Christopher O'Grady, Hanqi Guo, Yafan Huang
摘要
Over the last nearly 20 years, lossy compression has become an essential aspect of HPC applications’ data pipelines, allowing them to overcome limitations in storage capacity and bandwidth and, in some cases, increase computational throughput and capacity. However, with the adoption of lossy compression comes the requirement to assess and control the impact lossy compression has on scientific outcomes. In this work, we take a major step forward in describing the state of practice and by characterizing workloads. We examine applications’ needs and compressors’ capabilities across 9 different supercomputing application domains. We present 24 takeaways that provide best practices for applications, operational impacts for facilities achieving compressed data, and gaps in application needs not addressed by production compressors that point towards opportunities for future compression research.
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