human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "pangolin an efficient and flexible graph mining system on cpu and gpu"
  Abstract: There is growing interest in graph mining algorithms such as motif counting. Generic graph mining systems have been developed to provide unified interfaces for programming these algorithms. However, existing systems take minutes or even hours to mine even simple patterns in moderate-sized graphs, which significantly limits their real-world usability. We present Pangolin, a high-performance and flexible in-memory graph mining framework targeting both shared-memory CPUs and GPUs. Pangolin is the first graph mining system that supports GPU processing. We provide a simple embedding-centric programming interface based on the extend-reduce-filter model, which enables user to specify application-specific knowledge like aggressive enumeration search space pruning and isomorphism test elimination. We also describe novel optimizations that exploit locality, reduce memory consumption, and mitigate overheads of dynamic memory allocation and synchronization. Evaluation on a 28-core CPU demonstrates that Pangolin outperforms Arabesque and RStream, two state-of-the-art graph mining frameworks, by 49x and 88x on average, respectively. Acceleration on a V100 GPU further improves performance of Pangolin by 15x on average. Compared to state-of-the-art hand-optimized mining applications, Pangolin provides competitive performance with much less programming effort.

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.DC(Distributed, Parallel, and Cluster Computing)