PARSEC: PARallel Subgraph Enumeration in CUDA
2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS)(2022)
摘要
Subgraph enumeration is an important problem in the field of Graph Analytics with numerous applications. The problem is provably NP-complete and requires sophisticated heuristics and highly efficient implementations to be feasible on problem sizes of realistic scales. Parallel solutions have shown a lot of promise on CPUs and distributed environments. Recently, GPU-based parallel solutions have also been proposed to take advantage of the massive execution resources in modern GPUs. Subgraph enumeration involves traversing a search tree for each vertex of the data graph to find matches of a query in a graph. Most GPU-based solutions traverse the tree in breadth-first manner that exploits parallelism at the cost of high memory requirement and presents a formidable challenge for processing large graphs with high-degree vertices since the memory capacity of GPUs is significantly lower than that of CPUs. In this work, we propose a novel GPU solution based on a hybrid BFS and DFS approach where the top level(s) of the search trees are traversed in a fully parallel, breadth-first manner while each subtree is traversed in a more space-efficient, depth-first manner. The depth-first traversal of subtrees requires less memory but presents more challenges for parallel execution. To overcome the less parallel nature of depth-first traversal, we exploit fine-grained parallelism in each step of the depth-first traversal of sub-trees. We further identify and implement various optimizations to efficiently utilize memory and compute resources of the GPUs. We evaluate our performance in comparison with the state-of-the-art GPU and CPU implementations. We outperform the GPU and CPU implementations with a geometric mean speedup of 9.47× (up to 92.01×) and 2.37× (up to 12.70×), respectively. We also show that the proposed approach can efficiently process the graphs that previously cannot be processed by the state-of-the-art GPU solutions due to their excessive memory requirement.
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关键词
Nvidia GPU,CUDA,subgraph matching,subgraph isomorphism,graph pattern matching,parallel,hybrid BFS+DFS,DFS,tree traversal
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