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cuPC: CUDA-based Parallel PC Algorithm for Causal Structure Learning on GPU [article]

Behrooz Zarebavani, Foad Jafarinejad, Matin Hashemi, Saber Salehkaleybar
2019 arXiv   pre-print
In this paper, we propose a novel GPU-based parallel algorithm, called cuPC, to execute an order-independent version of PC.  ...  PC algorithm is one of the promising solutions to learn underlying causal structure by performing a number of conditional independence tests.  ...  In this paper, we propose a GPU-based parallel algorithm, called "cuPC", for learning causal structures based on PC-stable.  ... 
arXiv:1812.08491v3 fatcat:5rwiro6gcfehpa4apohynrua3e

Constraint-Based Causal Structure Learning in Multi-GPU Environments

Christopher Hagedorn, Johannes Huegle
2021 Lernen, Wissen, Daten, Analysen  
Learning causal structures from real-world high-dimensional data remains challenging due to algorithmic complexity and resulting long runtimes.  ...  Experiments on synthetic data show that explicit memory management is better suited for causal structure learning. On the one hand, it is faster than the version relying on UM by factors of up to 75.  ...  GPU-Accelerated Causal Structure Learning Based on the theoretical framework for causal reasoning [12] , causal relationships between observed variables are modeled in a Directed Acyclic Graph (DAG)  ... 
dblp:conf/lwa/HagedornH21 fatcat:g25qj2jui5aq7oxtcxu3agepfe