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 "graphulo implementation of server side sparse matrix multiply in the accumulo database"):
  Abstract: The Apache Accumulo database excels at distributed storage and indexing and is ideally suited for storing graph data. Many big data analytics compute on graph data and persist their results back to the database. These graph calculations are often best performed inside the database server. The GraphBLAS standard provides a compact and efficient basis for a wide range of graph applications through a small number of sparse matrix operations. In this article, we discuss a server-side implementation of GraphBLAS sparse matrix multiplication that leverages Accumulo's native, high-performance iterators. We compare the mathematics and performance of inner and outer product implementations, and show how an outer product implementation achieves optimal performance near Accumulo's peak write rate. We offer our work as a core component to the Graphulo library that will deliver matrix math primitives for graph analytics within Accumulo.

Includes members:
  Member "graphulo linear algebra graph kernels for nosql databases":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a systematic survey of general sparse matrix matrix multiplication")
  Member "achieving 100 000 000 database inserts per second using accumulo and d4m":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "75 000 000 000 streaming inserts second using hierarchical hypersparse graphblas matrices")
  Member "d4m 2 0 schema a general purpose high performance schema for the accumulo database":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "securing hpc using federated authentication")
  Member "standards for graph algorithm primitives":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a systematic survey of general sparse matrix matrix multiplication")
  Member "parallel sparse matrix matrix multiplication and indexing implementation and experiments":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the parallelism motifs of genomic data analysis")
  Member "highly parallel sparse matrix matrix multiplication":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a systematic survey of general sparse matrix matrix multiplication")

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.DB(Databases)