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Exact inference is a key problem in exploring probabilistic graphical models, where the computational complexity varies dramatically as the parameters of the graphical models changes. To achieve scalability over hundreds of threads remains a fundamental challenge. In this paper, we design an efficient scheduler hosted by the CPU to allocate cliques in junction trees to the GPGPU at run time. The scheduler can merge multiple small cliques or split large cliques dynamically so as to maximize thedoi:10.1109/icpp.2010.15 dblp:conf/icpp/JeonXP10 fatcat:4gntmnvifjf2lgzmiffmk2oapm