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: "robust massively parallel sorting"
  Abstract: We investigate distributed memory parallel sorting algorithms that scale to the largest available machines and are robust with respect to input size and distribution of the input elements. The main outcome is that four sorting algorithms cover the entire range of possible input sizes. For three algorithms we devise new low overhead mechanisms to make them robust with respect to duplicate keys and skewed input distributions. One of these, designed for medium sized inputs, is a new variant of quicksort with fast high-quality pivot selection. #R##N#At the same time asymptotic analysis provides performance guarantees and guides the selection and configuration of the algorithms. We validate these hypotheses using extensive experiments on 7 algorithms, 10 input distributions, up to 262144 cores, and varying input sizes over 9 orders of magnitude. For difficult input distributions, our algorithms are the only ones that work at all. For all but the largest input sizes, we are the first to perform experiments on such large machines at all and our algorithms significantly outperform the ones one would conventionally have considered.

Connected through hyperedge HE-1 (induced by source paper "communication efficient string sorting"):
  with members:
    - "scalable string and suffix sorting algorithms techniques and tools"
    - "engineering parallel string sorting"
    - "practical massively parallel sorting"
    - "parallel string sample sort"
    - "scalable distributed memory external sorting"

Connected through hyperedge HE-2 (induced by source paper "connected components on a pram in log diameter time"):
  with members:
    - "massively parallel algorithms for finding well connected components in sparse graphs"
    - "practical massively parallel sorting"
    - "communication steps for parallel query processing"
    - "sorting searching and simulation in the mapreduce framework"

Connected through hyperedge HE-3 (induced by source paper "engineering faster sorters for small sets of elements"):
  with members:
    - "scalable string and suffix sorting algorithms techniques and tools"
    - "in place parallel super scalar samplesort ips 4 o"
    - "twenty five comparators is optimal when sorting nine inputs and twenty nine for ten"
    - "parallel string sample sort"
    - "gpu sample sort"

Connected through hyperedge HE-4 (induced by source paper "parallel quicksort without pairwise element exchange"):
  with members:
    - "histogram sort with sampling"

Connected through hyperedge HE-5 (induced by source paper "lightweight mpi communicators with applications to perfectly balanced quicksort"):
  with members:
    - "efficient parallel random sampling vectorized cache efficient and online"
    - "practical massively parallel sorting"

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)