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: "petascale turbulence simulation using a highly parallel fast multipole method on gpus"
  Abstract: Abstract   This paper reports large-scale direct numerical simulations of homogeneous-isotropic fluid turbulence, achieving sustained performance of 1.08 petaflop/s on  gpu  hardware using single precision. The simulations use a vortex particle method to solve the Navier–Stokes equations, with a highly parallel fast multipole method ( fmm ) as numerical engine, and match the current record in mesh size for this application, a cube of      4096    3      computational points solved with a spectral method. The standard numerical approach used in this field is the pseudo-spectral method, relying on the  fft  algorithm as the numerical engine. The particle-based simulations presented in this paper quantitatively match the kinetic energy spectrum obtained with a pseudo-spectral method, using a trusted code. In terms of parallel performance, weak scaling results show the  fmm -based vortex method achieving 74% parallel efficiency on 4096 processes (one  gpu  per  mpi  process, 3  gpu s per node of the  tsubame -2.0 system). The  fft -based spectral method is able to achieve just 14% parallel efficiency on the same number of  mpi  processes (using only  cpu  cores), due to the all-to-all communication pattern of the  fft  algorithm. The calculation time for one time step was 108 s for the vortex method and 154 s for the spectral method, under these conditions. Computing with 69 billion particles, this work exceeds by an order of magnitude the largest vortex-method calculations to date.

Connected through hyperedge HE-1 (induced by source paper "fast multipole networks"):
  with members:
    - "wireless resilient routing reconfiguration"
    - "decentralized connectivity preserving deployment of large scale robot swarms"
    - "distributed cohesive control for robot swarms maintaining good connectivity in the presence of exterior forces"
    - "a tuned and scalable fast multipole method as a preeminent algorithm for exascale systems"

Connected through hyperedge HE-2 (induced by source paper "from piz daint to the stars simulation of stellar mergers using high level abstractions"):
  with members:
    - "data driven execution of fast multipole methods"

Connected through hyperedge HE-3 (induced by source paper "rpyfmm parallel adaptive fast multipole method for rotne prager yamakawa tensor in biomolecular hydrodynamics simulations"):
  with members:
    - "dashmm accelerated adaptive fast multipole poisson boltzmann solver on distributed memory architecture"

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"
    - "fast multipole preconditioners for sparse matrices arising from elliptic equations"
    - "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 "multiscale computing in the exascale era"):
  with members:
    - "exploiting data representation for fault tolerance"
    - "fabsim facilitating computational research through automation on large scale and distributed e infrastructures"
    - "an automated multiscale ensemble simulation approach for vascular blood flow"
    - "flexible composition and execution of high performance high fidelity multiscale biomedical simulations"
    - "survey of multiscale and multiphysics applications and communities"

Connected through hyperedge HE-6 (induced by source paper "fmm based vortex method for simulation of isotropic turbulence on gpus compared with a spectral method"):
  with members:
    - "hierarchical n body simulations with auto tuning for heterogeneous systems"
    - "petrbf a parallel o n algorithm for radial basis function interpolation with gaussians"

Connected through hyperedge HE-7 (induced by source paper "a tuned and scalable fast multipole method as a preeminent algorithm for exascale systems"):
  with members:
    - "biomolecular electrostatics using a fast multipole bem on up to 512 gpus and a billion unknowns"
    - "petfmm a dynamically load balancing parallel fast multipole library"

Connected through hyperedge HE-8 (induced by source paper "data driven execution of fast multipole methods"):
  with members:
    - "petfmm a dynamically load balancing parallel fast multipole library"

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)