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 "graph3s a simple speedy and scalable distributed graph processing system"):
  Abstract: Graph is a ubiquitous structure in many domains. The rapidly increasing data volume calls for efficient and scalable graph data processing. In recent years, designing distributed graph processing systems has been an increasingly important area to fulfil the demands of processing big graphs in a distributed environment. Though a variety of distributed graph processing systems have been developed, very little attention has been paid to achieving a good combinational system performance in terms of usage simplicity, efficiency and scalability. To contribute to the study of distributed graph processing system, this work tries to fill this gap by designing a simple, speedy and scalable system. Our observation is that enforcing the communication flexibility of a system leads to the gains of both system efficiency and scalability as well as simple usage. We realize our idea in a system Graph3S and conduct extensive experiments with diverse algorithms over big graphs from different domains to test its performance. The results show that, besides simple usage, our system has outstanding performance over various graph algorithms and can even reach up to two orders of magnitude speedup over existing in-memory systems when applying to some algorithms. Also, its scalability is competitive to disk-based systems and even better when less machines are used.

Includes members:
  Member "high level programming abstractions for distributed graph processing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "practice of streaming and dynamic graphs concepts models systems and parallelism")
  Member "start late or finish early a distributed graph processing system with redundancy reduction":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimizing ordered graph algorithms with graphit")
  Member "nxgraph an efficient graph processing system on a single machine":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hygcn a gcn accelerator with hybrid architecture")
  Member "effective techniques for message reduction and load balancing in distributed graph computation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "distributed edge partitioning for trillion edge graphs")
  Member "nscale neighborhood centric large scale graph analytics in the cloud":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "pruned landmark labeling meets vertex centric computation a surprisingly happy marriage")
  Member "flashgraph processing billion node graphs on an array of commodity ssds":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "semi asymmetric parallel graph algorithms for nvrams")
  Member "pregelix big ger graph analytics on a dataflow engine":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "learning key value store design")

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)