• DOI:10.14778/3317315.3317322
Corpus ID: 72941033

Accelerating Generalized Linear Models with MLWeaving: A One-Size-Fits-All System for Any-precision Learning

@article{Wang2019AcceleratingGL,
  title={Accelerating Generalized Linear Models with MLWeaving: A One-Size-Fits-All System for Any-precision Learning},
  author={Z. Wang and Kaan Kara and H. Zhang and G. Alonso and Onur Mutlu and Ce Zhang},
  journal={Proc. VLDB Endow.},
  year={2019},
  volume={12},
  pages={807-821}
}

Z. Wang, Kaan Kara, +3 authors Ce Zhang

Published 2019

Computer Science, Mathematics

Proc. VLDB Endow.

Learning from the data stored in a database is an important function increasingly available in relational engines. Methods using lower precision input data are of special interest given their overall higher efficiency but, in databases, these methods have a hidden cost: the quantization of the real value into a smaller number is an expensive step. To address the issue, in this paper we present MLWeaving, a data structure and hardware acceleration technique intended to speed up learning of… CONTINUE READING

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