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: "start late or finish early a distributed graph processing system with redundancy reduction"
  Abstract: Graph processing systems are important in the big data domain. However, processing graphs in parallel often introduces redundant computations in existing algorithms and models. Prior work has proposed techniques to optimize redundancies for the out-of-core graph systems, rather than the distributed graph systems. In this paper, we study various state-of-the-art distributed graph systems and observe root causes for these pervasively existing redundancies. To reduce redundancies without sacrificing parallelism, we further propose SLFE, a distributed graph processing system, designed with the principle of "start late or finish early". SLFE employs a novel preprocessing stage to obtain a graph's topological knowledge with negligible overhead. SLFE's redundancy-aware vertex-centric computation model can then utilize such knowledge to reduce the redundant computations at runtime. SLFE also provides a set of APIs to improve the programmability. Our experiments on an 8-node high-performance cluster show that SLFE outperforms all well-known distributed graph processing systems on real-world graphs (yielding up to 74.8x speedup). SLFE's redundancy-reduction schemes are generally applicable to other vertex-centric graph processing systems.

Connected through hyperedge HE-1 (induced by source paper "graph3s a simple speedy and scalable distributed graph processing system"):
  with members:
    - "high level programming abstractions for distributed graph processing"
    - "nxgraph an efficient graph processing system on a single machine"
    - "effective techniques for message reduction and load balancing in distributed graph computation"
    - "nscale neighborhood centric large scale graph analytics in the cloud"
    - "flashgraph processing billion node graphs on an array of commodity ssds"
    - "pregelix big ger graph analytics on a dataflow engine"

Connected through hyperedge HE-2 (induced by source paper "optimizing ordered graph algorithms with graphit"):
  with members:
    - "distributionally linearizable data structures"
    - "tiramisu a polyhedral compiler for expressing fast and portable code"
    - "gunrock gpu graph analytics"
    - "the gap benchmark suite"
    - "defining and evaluating network communities based on ground truth"

Connected through hyperedge HE-3 (induced by source paper "prioritygraph a unified programming model for optimizing ordered graph algorithms"):
  with members:
    - "distributionally linearizable data structures"
    - "gunrock gpu graph analytics"
    - "gunrock a high performance graph processing library on the gpu"
    - "the gap benchmark suite"
    - "defining and evaluating network communities based on ground truth"

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)