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 "roaring bitmaps implementation of an optimized software library"):
  Abstract: Compressed bitmap indexes are used in systems such as Git or Oracle to accelerate queries. They represent sets and often support operations such as unions, intersections, differences, and symmetric differences. Several important systems such as Elasticsearch, Apache Spark, Netflix's Atlas, LinkedIn's Pivot, Metamarkets' Druid, Pilosa, Apache Hive, Apache Tez, Microsoft Visual Studio Team Services and Apache Kylin rely on a specific type of compressed bitmap index called Roaring. We present an optimized software library written in C implementing Roaring bitmaps: CRoaring. It benefits from several algorithms designed for the single-instruction-multiple-data (SIMD) instructions available on commodity processors. In particular, we present vectorized algorithms to compute the intersection, union, difference and symmetric difference between arrays. We benchmark the library against a wide range of competitive alternatives, identifying weaknesses and strengths in our software. Our work is available under a liberal open-source license.

Includes members:
  Member "faster population counts using avx2 instructions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "quicker adc unlocking the hidden potential of product quantization with simd")
  Member "effortless data exploration with zenvisage an expressive and interactive visual analytics system":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "automated machine learning state of the art and open challenges")
  Member "consistently faster and smaller compressed bitmaps with roaring":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "techniques for inverted index compression")
  Member "array layouts for comparison based searching":
    also connected through other hyperedges:
      (none)
  Member "simd compression and the intersection of sorted integers":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "permute to train a new dimension to training deep neural networks")
  Member "better bitmap performance with roaring bitmaps":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a computational model for analytic column stores")
  Member "compressed bitmap indexes beyond unions and intersections":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "consistently faster and smaller compressed bitmaps with roaring")
  Member "reordering rows for better compression beyond the lexicographic order":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "consistently faster and smaller compressed bitmaps with roaring")

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)