98 citations · 108 across the 19 of their papers we have counts for
7 papers · 1 filter
LSHBloom: Memory-efficient, Extreme-scale Document Deduplication
Arham Khan, Robert Underwood, Carlo Siebenschuh +7
Contemporary large language model (LLM) training pipelines require the assembly of internet-scale databases full of text data from a variety of sources (e.g., web, academic, and pu…
LCP: Enhancing Scientific Data Management with Lossy Compression for Particles
Longtao Zhang, Ruoyu Li, Congrong Ren +10
Many scientific applications opt for particles instead of meshes as their basic primitives to model complex systems composed of billions of discrete entities. Such applications spa…
To Compress or Not To Compress: Energy Trade-Offs and Benefits of Lossy Compressed I/O
Grant Wilkins, Sheng Di, Jon C. Calhoun +2
Modern scientific simulations generate massive volumes of data, creating significant challenges for I/O and storage systems. Error-bounded lossy compression (EBLC) offers a solutio…
FRSZ2 for In-Register Block Compression Inside GMRES on GPUs
Thomas Grützmacher, Robert Underwood, Sheng Di +2
The performance of the GMRES iterative solver on GPUs is limited by the GPU main memory bandwidth. Compressed Basis GMRES outperforms GMRES by storing the Krylov basis in low preci…
HoSZp: An Efficient Homomorphic Error-bounded Lossy Compressor for Scientific Data
Tripti Agarwal, Sheng Di, Jiajun Huang +7
Error-bounded lossy compression has been a critical technique to significantly reduce the sheer amounts of simulation datasets for high-performance computing (HPC) scientific appli…
A Survey on Error-Bounded Lossy Compression for Scientific Datasets
Sheng Di, Jinyang Liu, Kai Zhao +23
Error-bounded lossy compression has been effective in significantly reducing the data storage/transfer burden while preserving the reconstructed data fidelity very well. Many error…
Understanding The Effectiveness of Lossy Compression in Machine Learning Training Sets
Robert Underwood, Jon C. Calhoun, Sheng Di +1
Learning and Artificial Intelligence (ML/AI) techniques have become increasingly prevalent in high performance computing (HPC). However, these methods depend on vast volumes of flo…