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 "relaxed scheduling for scalable belief propagation"):
  Abstract: The ability to leverage large-scale hardware parallelism has been one of the key enablers of the accelerated recent progress in machine learning. Consequently, there has been considerable effort invested into developing efficient parallel variants of classic machine learning algorithms. However, despite the wealth of knowledge on parallelization, some classic machine learning algorithms often prove hard to parallelize efficiently while maintaining convergence. In this paper, we focus on efficient parallel algorithms for the key machine learning task of inference on graphical models, in particular on the fundamental belief propagation algorithm. We address the challenge of efficiently parallelizing this classic paradigm by showing how to leverage scalable relaxed schedulers in this context. We present an extensive empirical study, showing that our approach outperforms previous parallel belief propagation implementations both in terms of scalability and in terms of wall-clock convergence time, on a range of practical applications.

Includes members:
  Member "message scheduling for performant many core belief propagation":
    also connected through other hyperedges:
      (none)
  Member "relaxed schedulers can efficiently parallelize iterative algorithms":
    also connected through other hyperedges:
      (none)
  Member "theoretically efficient parallel graph algorithms can be fast and scalable":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "semi asymmetric parallel graph algorithms for nvrams")
  Member "distributionally linearizable data structures":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimizing ordered graph algorithms with graphit")
  Member "parallelism in randomized incremental algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optimal parallel algorithms in the binary forking model")
  Member "the power of choice in priority scheduling":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "monotonically relaxing concurrent data structure semantics for performance an efficient 2d design framework")
  Member "the lock free k lsm relaxed priority queue":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "using skip graphs for increased numa locality")
  Member "greedy sequential maximal independent set and matching are parallel on average":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "polynomial pass lower bounds for graph streaming algorithms")

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)