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 "high quality shared memory graph partitioning"):
  Abstract: Partitioning graphs into blocks of roughly equal size such that few edges run between blocks is a frequently needed operation in processing graphs. Recently, size, variety, and structural complexity of these networks has grown dramatically. Unfortunately, previous approaches to parallel graph partitions have problems in this context since they often show a negative trade-off between speed and quality. We present an approach to multi-level shared-memory parallel graph partitioning that guarantees balanced solutions, shows high speedups for a variety of large graphs and yields very good quality independently of the number of cores used. For example, our algorithm partitions a graph with 2 billions edges using 16 cores in 53 seconds producing a solution that cuts two times less edges than our main competitor which runs 33 seconds. Important ingredients include parallel label propagation for both coarsening and improvement, parallel initial partitioning, a simple yet effective approach to parallel localized local search, and fast locality preserving hash tables.

Includes members:
  Member "in place parallel super scalar samplesort ips 4 o":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "engineering faster sorters for small sets of elements")
  Member "engineering parallel algorithms for community detection in massive networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "scaling up group closeness maximization")
  Member "concurrent hash tables fast and general":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "finding all global minimum cuts in practice")
  Member "parallel graph partitioning for complex networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multilevel acyclic hypergraph partitioning")
  Member "partitioning complex networks via size constrained clustering":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "scalable graph algorithms")
  Member "recent advances in graph partitioning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "multilevel acyclic hypergraph partitioning")
  Member "the power of simple tabulation hashing":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "tight static lower bounds for non adaptive data structures")
  Member "n level graph partitioning":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "multilevel acyclic hypergraph partitioning")

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.DS(Data Structures and Algorithms)