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: "dynamic load balancing techniques for particulate flow simulations"
  Abstract: Parallel multiphysics simulations often suffer from load imbalances originating from the applied coupling of algorithms with spatially and temporally varying workloads. It is thus desirable to minimize these imbalances to reduce the time to solution and to better utilize the available hardware resources. Taking particulate flows as an illustrating example application, we present and evaluate load balancing techniques that tackle this challenging task. This involves a load estimation step in which the currently generated workload is predicted. We describe in detail how such a workload estimator can be developed. In a second step, load distribution strategies like space-filling curves or graph partitioning are applied to dynamically distribute the load among the available processes. To compare and analyze their performance, we employ these techniques to a benchmark scenario and observe a reduction of the load imbalances by almost a factor of four. This results in a decrease of the overall runtime by 14% for space-filling curves.

Connected through hyperedge HE-1 (induced by source paper "walberla a block structured high performance framework for multiphysics simulations"):
  with members:
    - "a modular and extensible software architecture for particle dynamics"
    - "lattice boltzmann benchmark kernels as a testbed for performance analysis"
    - "extreme scale block structured adaptive mesh refinement"
    - "the maximum dissipation principle in rigid body dynamics with inelastic impacts"
    - "a local parallel communication algorithm for polydisperse rigid body dynamics"
    - "a comparative study of fluid particle coupling methods for fully resolved lattice boltzmann simulations"
    - "a scalable and extensible checkpointing scheme for massively parallel simulations"
    - "a coupled lattice boltzmann method and discrete element method for discrete particle simulations of particulate flows"

Connected through hyperedge HE-2 (induced by source paper "a modular and extensible software architecture for particle dynamics"):
  with members:
    - "extreme scale block structured adaptive mesh refinement"
    - "a local parallel communication algorithm for polydisperse rigid body dynamics"
    - "a domain specific language for performance portable molecular dynamics algorithms"
    - "massively parallel algorithms for the lattice boltzmann method on nonuniform grids"
    - "ultrascale simulations of non smooth granular dynamics"

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)