GPUCSL: GPU-Based Library for Causal Structure Learning

被引:1
作者
Braun, Tom [1 ]
Hurdelhey, Ben [1 ]
Meier, Dominik [1 ]
Tsayun, Petr [1 ]
机构
[1] Univ Potsdam, Hasso Plattner Inst, Potsdam, Germany
来源
2022 IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS, ICDMW | 2022年
关键词
Causal Structure Learning; PC Algorithm; GPU Acceleration; CUDA; !text type='Python']Python[!/text;
D O I
10.1109/ICDMW58026.2022.00159
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
GPUCSL is a maintainable and extensible Python library for GPU-accelerated causal structure learning (CSL) based on the PC algorithm. The library supports multivariate normal and discrete distributed data, and implements multi-GPU support for multivariate normal distributed data. GPUCSL combines several stand-alone independent research implementations to allow a unified entry point into GPU-accelerated CSL. The library outperforms CPU-based implementations with an average speedup factor of 9.5 against pcalg and 19.8 against bnlearn and remains within the order of magnitude of existing GPU-accelerated CSL research. The source code is available at https://github.com/hpi- epic/gpucsl.
引用
收藏
页码:1236 / 1239
页数:4
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