human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "design generation and validation of extreme scale power law graphs"):
  Abstract: Massive power-law graphs drive many fields: metagenomics, brain mapping, Internet-of-things, cybersecurity, and sparse machine learning. The development of novel algorithms and systems to process these data requires the design, generation, and validation of enormous graphs with exactly known properties. Such graphs accelerate the proper testing of new algorithms and systems and are a prerequisite for success on real applications. Many random graph generators currently exist that require realizing a graph in order to know its exact properties: number of vertices, number of edges, degree distribution, and number of triangles. Designing graphs using these random graph generators is a time-consuming trial-and-error process. This paper presents a novel approach that uses Kronecker products to allow the exact computation of graph properties prior to graph generation. In addition, when a real graph is desired, it can be generated quickly in memory on a parallel computer with no-interprocessor communication. To test this approach, graphs with 1012 edges are generated on a 40,000+ core supercomputer in 1 second and exactly agree with those predicted by the theory. In addition, to demonstrate the extensibility of this approach, decetta-scale graphs with up to 10^30 edges are simulated in a few minutes on a laptop.

Includes members:
  Member "streaming graph challenge stochastic block partition":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "75 000 000 000 streaming inserts second using hierarchical hypersparse graphblas matrices")
  Member "distributed triangle counting in the graphulo matrix math library":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "graphchallenge org raising the bar on graph analytic performance")
  Member "preconditioned spectral clustering for stochastic block partition streaming graph challenge preliminary version at arxiv":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "graphchallenge org raising the bar on graph analytic performance")
  Member "constructing adjacency arrays from incidence arrays":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "polystore mathematics of relational algebra")
  Member "an ensemble framework for detecting community changes in dynamic networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "graphchallenge org raising the bar on graph analytic performance")
  Member "scaling in internet traffic a 14 year and 3 day longitudinal study with multiscale analyses and random projections":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "new phenomena in large scale internet traffic")
  Member "static graph challenge subgraph isomorphism":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a systematic survey of general sparse matrix matrix multiplication")
  Member "enabling massive deep neural networks with the graphblas":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "ai data wrangling with associative arrays")

Question: Please tell me which class the source paper 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)