In this paper, parallelization techniques are proposed for the branch-and-bound algorithm OTClique for the maximum weight clique problem. OTClique consists of the precomputation phase and the branch-and-bound phase. The proposed algorithm parallelizes both of them. In the precomputation phase, the construction of optimal tables is parallelized. In the branch-and-bound phase, the proposed algorithm generates small subproblems and assigns them to threads. A technique to share lower and upper bounds is also proposed. Experiments using some benchmarks show that the proposed parallelization techniques improve the performance of OTClique. With an 8-core CPU, the computation time of OTClique becomes 6.91 times shorter on random graphs and 5.38 times on DIMACS benchmarks on average.

在本文中，针对最大权重集团问题的分支定界算法OTClique提出了并行化技术。OTClique包含预计算阶段和分支定界阶段。所提出的算法使两者并行化。在预计算阶段，优化表的构造是并行的。在分支定界阶段，所提出的算法生成小的子问题并将其分配给线程。还提出了共享上下限的技术。使用一些基准的实验表明，所提出的并行化技术提高了OTClique的性能。使用8核CPU时，OTClique的计算时间在随机图形上平均缩短了6.91倍，在DIMACS基准上平均缩短了5.38倍。