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: "fast multipole preconditioners for sparse matrices arising from elliptic equations"
  Abstract: Among optimal hierarchical algorithms for the computational solution of elliptic problems, the Fast Multipole Method (FMM) stands out for its adaptability to emerging architectures, having high arithmetic intensity, tunable accuracy, and relaxable global synchronization requirements. We demonstrate that, beyond its traditional use as a solver in problems for which explicit free-space kernel representations are available, the FMM has applicability as a preconditioner in finite domain elliptic boundary value problems, by equipping it with boundary integral capability for satisfying conditions at finite boundaries and by wrapping it in a Krylov method for extensibility to more general operators. Here, we do not discuss the well developed applications of FMM to implement matrix-vector multiplications within Krylov solvers of boundary element methods. Instead, we propose using FMM for the volume-to-volume contribution of inhomogeneous Poisson-like problems, where the boundary integral is a small part of the overall computation. Our method may be used to precondition sparse matrices arising from finite difference/element discretizations, and can handle a broader range of scientific applications. Compared with multigrid methods, it is capable of comparable algebraic convergence rates down to the truncation error of the discretized PDE, and it offers potentially superior multicore and distributed memory scalability properties on commodity architecture supercomputers. Compared with other methods exploiting the low rank character of off-diagonal blocks of the dense resolvent operator, FMM-preconditioned Krylov iteration may reduce the amount of communication because it is matrix-free and exploits the tree structure of FMM. We describe our tests in reproducible detail with freely available codes and outline directions for further extensibility.

Connected through hyperedge HE-1 (induced by source paper "fft fmm and multigrid on the road to exascale performance challenges and opportunities"):
  with members:
    - "communication reducing algorithms for distributed hierarchical n body problems with boundary distributions"
    - "fast multipole method as a matrix free hierarchical low rank approximation"
    - "an fmm based on dual tree traversal for many core architectures"

Connected through hyperedge HE-2 (induced by source paper "extreme scale fmm accelerated boundary integral equation solver for wave scattering"):
  with members:
    - "communication reducing algorithms for distributed hierarchical n body problems with boundary distributions"
    - "an fmm based on dual tree traversal for many core architectures"
    - "petfmm a dynamically load balancing parallel fast multipole library"

Connected through hyperedge HE-3 (induced by source paper "learning with analytical models"):
  with members:
    - "optimization of an electromagnetics code with multicore wavefront diamond blocking and multi dimensional intra tile parallelization"
    - "communication complexity of the fast multipole method and its algebraic variants"
    - "an fmm based on dual tree traversal for many core architectures"

Connected through hyperedge HE-4 (induced by source paper "fast multipole method as a matrix free hierarchical low rank approximation"):
  with members:
    - "a fast block low rank dense solver with applications to finite element matrices"
    - "a distributed memory package for dense hierarchically semi separable matrix computations using randomization"
    - "askit approximate skeletonization kernel independent treecode in high dimensions"
    - "petascale turbulence simulation using a highly parallel fast multipole method on gpus"
    - "biomolecular electrostatics using a fast multipole bem on up to 512 gpus and a billion unknowns"

Connected through hyperedge HE-5 (induced by source paper "communication complexity of the fast multipole method and its algebraic variants"):
  with members:
    - "asynchronous execution of the fast multipole method using charm"
    - "a performance model for the communication in fast multipole methods on hpc platforms"

Connected through hyperedge HE-6 (induced by source paper "petiga a framework for high performance isogeometric analysis"):
  with members:
    - "extreme scale multigrid components within petsc"
    - "the cost of continuity performance of iterative solvers on isogeometric finite elements"

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.NA(Numerical Analysis)