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: "on the efficiency of localized work stealing"
  Abstract: Abstract   This paper investigates a variant of the work-stealing algorithm that we call the  localized work-stealing algorithm . The intuition behind this variant is that because of locality, processors can benefit from working on their own work. Consequently, when a processor is free, it makes a steal attempt to get back its own work. We call this type of steal a  steal-back . We show that the expected running time of the algorithm is      T    1    /  P  +  O  (    T    ∞    P  )   , and that under the “even distribution of free agents assumption”, the expected running time of the algorithm is      T    1    /  P  +  O  (    T    ∞    lg  ⁡  P  )   . In addition, we obtain another running-time bound based on ratios between the sizes of serial tasks in the computation. If  M  denotes the maximum ratio between the largest and the smallest serial tasks of a processor after removing a total of    O  (  P  )    serial tasks across all processors from consideration, then the expected running time of the algorithm is      T    1    /  P  +  O  (    T    ∞    M  )   .

Connected through hyperedge HE-1 (induced by source paper "a numa aware provably efficient task parallel platform based on the work first principle"):
  with members:
    - "parallel work inflation memory effects and their empirical analysis"

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)