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: "fast parallel operations on search trees"
  Abstract: Using (a,b)-trees as an example, we show how to perform a parallel split with logarithmic latency and parallel join, bulk updates, intersection, union (or merge), and (symmetric) set difference with logarithmic latency and with information theoretically optimal work. We present both asymptotically optimal solutions and simplified versions that perform well in practice - they are several times faster than previous implementations.

Connected through hyperedge HE-1 (induced by source paper "communication efficient weighted reservoir sampling from fully distributed data streams"):
  with members:
    - "optimal random sampling from distributed streams revisited"
    - "weighted reservoir sampling from distributed streams"
    - "parallel weighted random sampling"
    - "parallel streaming random sampling"
    - "efficient parallel random sampling vectorized cache efficient and online"
    - "weighted sampling without replacement from data streams"

Connected through hyperedge HE-2 (induced by source paper "optimal parallel algorithms in the binary forking model"):
  with members:
    - "parallel finger search structures"
    - "theoretically efficient parallel graph algorithms can be fast and scalable"
    - "parallel write efficient algorithms and data structures for computational geometry"
    - "parallel working set search structures"
    - "parallelism in randomized incremental algorithms"
    - "pam parallel augmented maps"
    - "resource oblivious sorting on multicores"
    - "parallel ordered sets using join"

Connected through hyperedge HE-3 (induced by source paper "parallel batch dynamic graph connectivity"):
  with members:
    - "theoretically efficient parallel graph algorithms can be fast and scalable"
    - "parallel working set search structures"
    - "improved worst case deterministic parallel dynamic minimum spanning forest"
    - "pam parallel augmented maps"
    - "batch parallel euler tour trees"
    - "near optimal parallel algorithms for dynamic dfs in undirected graphs"
    - "the ubiquity of large graphs and surprising challenges of graph processing"
    - "fully dynamic connectivity in o log n log log n 2 amortized expected time"

Connected through hyperedge HE-4 (induced by source paper "parallel finger search structures"):
  with members:
    - "optimal parallel algorithms in the binary forking model"
    - "optimal multithreaded batch parallel 2 3 trees"
    - "parallel working set search structures"
    - "batch parallel euler tour trees"
    - "parallel combining benefits of explicit synchronization"
    - "a general technique for non blocking trees"
    - "flat combining and the synchronization parallelism tradeoff"

Connected through hyperedge HE-5 (induced by source paper "communication efficient weighted reservoir sampling"):
  with members:
    - "optimal random sampling from distributed streams revisited"
    - "weighted reservoir sampling from distributed streams"
    - "parallel weighted random sampling"
    - "weighted sampling without replacement from data streams"
    - "practical massively parallel sorting"
    - "weighted random sampling over data streams"

Connected through hyperedge HE-6 (induced by source paper "optimal multithreaded batch parallel 2 3 trees"):
  with members:
    - "optimal parallel algorithms in the binary forking model"
    - "parallel finger search structures"
    - "parallel working set search structures"

Connected through hyperedge HE-7 (induced by source paper "parallel write efficient algorithms and data structures for computational geometry"):
  with members:
    - "algorithmic building blocks for asymmetric memories"
    - "parallelism in randomized incremental algorithms"
    - "pam parallel augmented maps"
    - "sorting with asymmetric read and write costs"
    - "efficient algorithms with asymmetric read and write costs"
    - "wear minimization for cuckoo hashing how not to throw a lot of eggs into one basket"

Connected through hyperedge HE-8 (induced by source paper "pam parallel augmented maps"):
  with members:
    - "range queries in non blocking k ary search trees"
    - "a general technique for non blocking trees"
    - "fast set intersection in memory"

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)