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: "qr factorization of tall and skinny matrices in a grid computing environment"
  Abstract: Previous studies have reported that common dense linear algebra operations do not achieve speed up by using multiple geographical sites of a computational grid. Because such operations are the building blocks of most scientific applications, conventional supercomputers are still strongly predominant in high-performance computing and the use of grids for speeding up large-scale scientific problems is limited to applications exhibiting parallelism at a higher level. We have identified two performance bottlenecks in the distributed memory algorithms implemented in ScaLAPACK, a state-of-the-art dense linear algebra library. First, because ScaLA-PACK assumes a homogeneous communication network, the implementations of ScaLAPACK algorithms lack locality in their communication pattern. Second, the number of messages sent in the ScaLAPACK algorithms is significantly greater than other algorithms that trade flops for communication. In this paper, we present a new approach for computing a QR factorization – one of the main dense linear algebra kernels – of tall and skinny matrices in a grid computing environment that overcomes these two bottlenecks. Our contribution is to articulate a recently proposed algorithm (Communication Avoiding QR) with a topology-aware middleware (QCG-OMPI) in order to confine intensive communications (ScaLAPACK calls) within the different geographical sites. An experimental study conducted on the Grid'5000 platform shows that the resulting performance increases linearly with the number of geographical sites on large-scale problems (and is in particular consistently higher than ScaLAPACK's).

Connected through hyperedge HE-1 (induced by source paper "fault tolerant qr factorization for general matrices"):
  with members:
    - "exploiting redundant computation in communication avoiding algorithms for algorithm based fault tolerance"

Connected through hyperedge HE-2 (induced by source paper "scalable methods for nonnegative matrix factorizations of near separable tall and skinny matrices"):
  with members:
    - "direct qr factorizations for tall and skinny matrices in mapreduce architectures"
    - "computing a nonnegative matrix factorization provably"
    - "on the complexity of nonnegative matrix factorization"

Connected through hyperedge HE-3 (induced by source paper "multilevel communication optimal lu and qr factorizations for hierarchical platforms"):
  with members:
    - "minimizing communication in linear algebra"

Connected through hyperedge HE-4 (induced by source paper "iterative row sampling"):
  with members:
    - "low rank approximation and regression in input sparsity time"
    - "osnap faster numerical linear algebra algorithms via sparser subspace embeddings"
    - "low distortion subspace embeddings in input sparsity time and applications to robust linear regression"
    - "faster spectral sparsification and numerical algorithms for sdd matrices"
    - "the fast cauchy transform and faster robust linear regression"
    - "effective stiffness generalizing effective resistance sampling to finite element matrices"
    - "near optimal column based matrix reconstruction"
    - "row sampling for matrix algorithms via a non commutative bernstein bound"

Connected through hyperedge HE-5 (induced by source paper "tiled qr factorization algorithms"):
  with members:
    - "communication optimal parallel and sequential qr and lu factorizations theory and practice"
    - "a class of parallel tiled linear algebra algorithms for multicore architectures"

Connected through hyperedge HE-6 (induced by source paper "hierarchical qr factorization algorithms for multi core cluster systems"):
  with members:
    - "tiled qr factorization algorithms"
    - "a class of parallel tiled linear algebra algorithms for multicore architectures"

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)