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: "optimal multithreaded batch parallel 2 3 trees"
  Abstract: This paper presents a batch-parallel 2-3 tree T in the asynchronous PPM (parallel pointer machine) model that supports searches, insertions and deletions in sorted batches and has essentially optimal parallelism, even under the QRMW (queued read-modify-write) memory model where concurrent memory accesses to the same location are queued and serviced one by one. #R##N#Specifically, if T has n items, then performing an item-sorted batch of b operations on T takes only O( b * log(n/b+1) + b ) work and O( log b + log n ) span (in the worst case as b,n -> inf). This is information-theoretically work-optimal for b <= n, and also span-optimal in the PPM model. The input batch can be any balanced binary tree, and hence T can also be used to implement sorted sets supporting optimal intersection, union and difference of sets with sizes m <= n in O( m * log(n/m+1) ) work and O( log m + log n ) span. #R##N#To the author's knowledge, T is the first parallel sorted-set data structure with these performance bounds that can be used in an asynchronous multi-processor machine under a memory model with queued contention. This is unlike PRAM data structures such as the PVW 2-3 tree (by Paul, Vishkin and Wagener), which rely on lock-step synchronicity of the processors. In fact, T is designed to have bounded contention and satisfy the claimed work and span bounds regardless of the execution schedule. #R##N#All data structures and algorithms in this paper fit into the dynamic multithreading paradigm. Also, as a consequence of working in the asynchronous PPM model, all their performance bounds are directly composable with those of other data structures and algorithms in the same model.

Connected through hyperedge HE-1 (induced by source paper "parallel finger search structures"):
  with members:
    - "optimal parallel algorithms in the binary forking model"
    - "parallel working set search structures"
    - "batch parallel euler tour trees"
    - "parallel combining benefits of explicit synchronization"
    - "a general technique for non blocking trees"
    - "fast parallel operations on search trees"
    - "flat combining and the synchronization parallelism tradeoff"

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.DS(Data Structures and Algorithms)