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: "massively parallel sort merge joins in main memory multi core database systems"
  Abstract: Two emerging hardware trends will dominate the database system technology in the near future: increasing main memory capacities of several TB per server and massively parallel multi-core processing. Many algorithmic and control techniques in current database technology were devised for disk-based systems where I/O dominated the performance. In this work we take a new look at the well-known sort-merge join which, so far, has not been in the focus of research in scalable massively parallel multi-core data processing as it was deemed inferior to hash joins. We devise a suite of new massively parallel sort-merge (MPSM) join algorithms that are based on partial partition-based sorting. Contrary to classical sort-merge joins, our MPSM algorithms do not rely on a hard to parallelize final merge step to create one complete sort order. Rather they work on the independently created runs in parallel. This way our MPSM algorithms are NUMA-affine as all the sorting is carried out on local memory partitions. An extensive experimental evaluation on a modern 32-core machine with one TB of main memory proves the competitive performance of MPSM on large main memory databases with billions of objects. It scales (almost) linearly in the number of employed cores and clearly outperforms competing hash join proposals - in particular it outperforms the "cutting-edge" Vectorwise parallel query engine by a factor of four.

Connected through hyperedge HE-1 (induced by source paper "streambox tz secure stream analytics at the edge with trustzone"):
  with members:
    - "securestreams a reactive middleware framework for secure data stream processing"
    - "trustshadow secure execution of unmodified applications with arm trustzone"
    - "c flat control flow attestation for embedded systems software"
    - "armageddon cache attacks on mobile devices"
    - "efficient system enforced deterministic parallelism"

Connected through hyperedge HE-2 (induced by source paper "streambox hbm stream analytics on high bandwidth hybrid memory"):
  with members:
    - "scaling deep learning on gpu and knights landing clusters"
    - "exploring the performance benefit of hybrid memory system on hpc environments"
    - "fast sorting algorithms using avx 512 on intel knights landing"
    - "bigdatabench a big data benchmark suite from internet services"

Connected through hyperedge HE-3 (induced by source paper "streambox tz a secure iot analytics engine at the edge"):
  with members:
    - "securestreams a reactive middleware framework for secure data stream processing"
    - "trustshadow secure execution of unmodified applications with arm trustzone"
    - "armageddon cache attacks on mobile devices"

Connected through hyperedge HE-4 (induced by source paper "a memory bandwidth efficient hybrid radix sort on gpus"):
  with members:
    - "deterministic sample sort for gpus"
    - "gpu sample sort"

Connected through hyperedge HE-5 (induced by source paper "pi a parallel in memory skip list based index"):
  with members:
    - "pragmatic primitives for non blocking data structures"

Connected through hyperedge HE-6 (induced by source paper "dimmwitted a study of main memory statistical analytics"):
  with members:
    - "an approximate efficient solver for lp rounding"
    - "near optimal coresets for least squares regression"
    - "mli an api for distributed machine learning"
    - "the madlib analytics library or mad skills the sql"
    - "distributed graphlab a framework for machine learning in the cloud"
    - "building high level features using large scale unsupervised learning"
    - "a reliable effective terascale linear learning system"
    - "measuring numa effects with the stream benchmark"

Connected through hyperedge HE-7 (induced by source paper "main memory adaptive indexing for multi core systems"):
  with members:
    - "concurrency control for adaptive indexing"
    - "stochastic database cracking towards robust adaptive indexing in main memory column stores"

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.DB(Databases)