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: "lattice boltzmann benchmark kernels as a testbed for performance analysis"
  Abstract: Abstract   Lattice Boltzmann methods (LBM) are an important part of current computational fluid dynamics (CFD). They allow easy implementations and boundary handling. However, competitive time to solution not only depends on the choice of a reasonable method, but also on an efficient implementation on modern hardware. Hence, performance optimization has a long history in the lattice Boltzmann community. A variety of options exists regarding the implementation with direct impact on the solver performance. Experimenting and evaluating each option often is hard as the kernel itself is typically embedded in a larger code base. With our suite of lattice Boltzmann kernels we provide the infrastructure for such endeavors. Already included are several kernels ranging from simple to fully optimized implementations. Although these kernels are not fully functional CFD solvers, they are equipped with a solid verification method. The kernels may act as an reference for performance comparisons and as a blue print for optimization strategies. In this paper we give an overview of already available kernels, establish a performance model for each kernel, and show a comparison of implementations and recent architectures.

Connected through hyperedge HE-1 (induced by source paper "lbmpy a flexible code generation toolkit for highly efficient lattice boltzmann simulations"):
  with members:
    - "walberla a block structured high performance framework for multiphysics simulations"
    - "a python extension for the massively parallel multiphysics simulation framework walberla"
    - "comparison of different propagation steps for lattice boltzmann methods"
    - "likwid a lightweight performance oriented tool suite for x86 multicore environments"
    - "likwid a lightweight performance oriented tool suite for x86 multicore environments"

Connected through hyperedge HE-2 (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"
    - "extreme scale block structured adaptive mesh refinement"
    - "dynamic load balancing techniques for particulate flow simulations"
    - "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-3 (induced by source paper "dynamic load balancing techniques for particulate flow simulations"):
  with members:
    - "extreme scale block structured adaptive mesh refinement"
    - "a comparative study of fluid particle coupling methods for fully resolved lattice boltzmann simulations"
    - "kerncraft a tool for analytic performance modeling of loop kernels"
    - "massively parallel algorithms for the lattice boltzmann method on nonuniform grids"
    - "ultrascale simulations of non smooth granular dynamics"
    - "recent advances in graph partitioning"
    - "likwid a lightweight performance oriented tool suite for x86 multicore environments"
    - "likwid a lightweight performance oriented tool suite for x86 multicore environments"

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.PF(Performance)