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: "pt scotch a tool for efficient parallel graph ordering"
  Abstract: The parallel ordering of large graphs is a difficult problem, because on the one hand minimum degree algorithms do not parallelize well, and on the other hand the obtainment of high quality orderings with the nested dissection algorithm requires efficient graph bipartitioning heuristics, the best sequential implementations of which are also hard to parallelize. This paper presents a set of algorithms, implemented in the PT-Scotch software package, which allows one to order large graphs in parallel, yielding orderings the quality of which is only slightly worse than the one of state-of-the-art sequential algorithms. Our implementation uses the classical nested dissection approach but relies on several novel features to solve the parallel graph bipartitioning problem. Thanks to these improvements, PT-Scotch produces consistently better orderings than ParMeTiS on large numbers of processors.

Connected through hyperedge HE-1 (induced by source paper "an optimized parallel computation of the ghost layer for adaptive hybrid forest meshes"):
  with members:
    - "parallel tree algorithms for amr and non standard data access"
    - "scalable algorithms for parallel tree based adaptive mesh refinement with general element types"
    - "massively parallel algorithms for the lattice boltzmann method on nonuniform grids"
    - "a tetrahedral space filling curve for nonconforming adaptive meshes"
    - "coarse mesh partitioning for tree based amr"
    - "recursive algorithms for distributed forests of octrees"
    - "the dune alugrid module"

Connected through hyperedge HE-2 (induced by source paper "nektar enhancing the capability and application of high fidelity spectral hp element methods"):
  with members:
    - "a semi structured approach to curvilinear mesh generation around streamlined bodies"
    - "high order curvilinear hybrid mesh generation for cfd simulations"

Connected through hyperedge HE-3 (induced by source paper "scalable computation of thermomechanical turbomachinery problems"):
  with members:
    - "dolfin automated finite element computing"
    - "mesh algorithms for pde with sieve i mesh distribution"

Connected through hyperedge HE-4 (induced by source paper "dynamic load balancing techniques for particulate flow simulations"):
  with members:
    - "lattice boltzmann benchmark kernels as a testbed for performance analysis"
    - "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"

Connected through hyperedge HE-5 (induced by source paper "a performance spectrum for parallel computational frameworks that solve pdes"):
  with members:
    - "firedrake automating the finite element method by composing abstractions"
    - "large scale optimization based non negative computational framework for diffusion equations parallel implementation and performance studies"
    - "variational inequality approach to enforcing the non negative constraint for advection diffusion equations"
    - "finite element integration on gpus"
    - "hitting the memory wall implications of the obvious"

Connected through hyperedge HE-6 (induced by source paper "loom query aware partitioning of online graphs"):
  with members:
    - "taper query aware partition enhancement for large heterogenous graphs"
    - "a selectivity based approach to continuous pattern detection in streaming graphs"
    - "query workload based rdf graph fragmentation and allocation"
    - "provgen generating synthetic prov graphs with predictable structure"
    - "practical graph isomorphism ii"

Connected through hyperedge HE-7 (induced by source paper "ghost building blocks for high performance sparse linear algebra on heterogeneous systems"):
  with members:
    - "pipelined iterative solvers with kernel fusion for graphics processing units"
    - "performance engineering of the kernel polynomal method on large scale cpu gpu systems"
    - "a unified sparse matrix data format for efficient general sparse matrix vector multiplication on modern processors with wide simd units"
    - "asynchronous mpi for the masses"
    - "density matrix based algorithm for solving eigenvalue problems"

Connected through hyperedge HE-8 (induced by source paper "a meta graph approach to analyze subgraph centric distributed programming models"):
  with members:
    - "predictive partitioning for efficient bfs traversal in social networks"
    - "goffish a sub graph centric framework for large scale graph analytics"

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)