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: "well structured futures and cache locality"
  Abstract: In \emph{fork-join parallelism}, a sequential program is split into a directed acyclic graph of tasks linked by directed dependency edges, and the tasks are executed, possibly in parallel, in an order consistent with their dependencies. A popular and effective way to extend fork-join parallelism is to allow threads to create \emph{futures}. A thread creates a future to hold the results of a computation, which may or may not be executed in parallel. That result is returned when some thread \emph{touches} that future, blocking if necessary until the result is ready. #R##N#Recent research has shown that while futures can, of course, enhance parallelism in a structured way, they can have a deleterious effect on cache locality. In the worst case, futures can incur $\Omega(P T_\infty + t T_\infty)$ deviations, which implies $\Omega(C P T_\infty + C t T_\infty)$ additional cache misses, where $C$ is the number of cache lines, $P$ is the number of processors, $t$ is the number of touches, and $T_\infty$ is the \emph{computation span}. Since cache locality has a large impact on software performance on modern multicores, this result is troubling. #R##N#In this paper, however, we show that if futures are used in a simple, disciplined way, then the situation is much better: if each future is touched only once, either by the thread that created it, or by a later descendant of the thread that created it, then parallel executions with work stealing can incur at most $O(C P T^2_\infty)$ additional cache misses, a substantial improvement. This structured use of futures is characteristic of many (but not all) parallel applications.

Connected through hyperedge HE-1 (induced by source paper "adapting persistent data structures for concurrency and speculation"):
  with members:
    - "distributionally linearizable data structures"
    - "pam parallel augmented maps"
    - "pragmatic primitives for non blocking data structures"
    - "techniques for constructing efficient lock free data structures"
    - "a general technique for non blocking trees"
    - "non determinism in byzantine fault tolerant replication"
    - "flat combining and the synchronization parallelism tradeoff"
    - "a critique of ansi sql isolation levels"

Connected through hyperedge HE-2 (induced by source paper "nested dataflow algorithms for dynamic programming recurrences with more than o 1 dependency"):
  with members:
    - "extending the nested parallel model to the nested dataflow model with provably efficient schedulers"

Connected through hyperedge HE-3 (induced by source paper "efficient race detection with futures"):
  with members:
    - "dynamic race prediction in linear time"

Connected through hyperedge HE-4 (induced by source paper "extending the nested parallel model to the nested dataflow model with provably efficient schedulers"):
  with members:
    - "efficient resource oblivious algorithms for multicores"
    - "minimizing communication in linear algebra"

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)