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: "rpyfmm parallel adaptive fast multipole method for rotne prager yamakawa tensor in biomolecular hydrodynamics simulations"
  Abstract: Abstract   RPYFMM is a software package for the efficient evaluation of the potential field governed by the Rotne–Prager–Yamakawa (RPY) tensor interactions in biomolecular hydrodynamics simulations. In our algorithm, the RPY tensor is decomposed as a linear combination of four Laplace interactions, each of which is evaluated using the adaptive fast multipole method (FMM) (Greengard and Rokhlin, 1997) where the exponential expansions are applied to diagonalize the multipole-to-local translation operators. RPYFMM offers a unified execution on both shared and distributed memory computers by leveraging the DASHMM library (DeBuhr et al., 2016, 2018). Preliminary numerical results show that the interactions for a molecular system of 15 million particles (beads) can be computed within one second on a Cray XC30 cluster using 12,288 cores, while achieving approximately 54% strong-scaling efficiency.    Program summary  Program Title: RPYFMM: Parallel Adaptive FMM for RPY Tensor  Program Files doi:  http://dx.doi.org/10.17632/zpbjvy8whp.1 #N#              Licensing provisions: BSD 3-clause  Programming language: C++  Nature of problem: Evaluate the Rotne–Prager–Yamakawa tensor matrix–vector multiplications describing the hydrodynamics interaction in biomolecular systems.  Solution method: The Rotne–Prager–Yamakawa tensor is decomposed as a linear combination of four Laplace interactions, each of which is evaluated using the new version of adaptive fast multipole method [1].  Additional Comments: RPYFMM is built on top of the DASHMM library and the Asynchronous Multi-Tasking HPX-5 runtime system. DASHMM is automatically downloaded during installation and HPX-5 is available at  http://hpx.crest.iu.edu/ .

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)