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: "bsp vs mapreduce"
  Abstract: Abstract   The MapReduce framework has been generating a lot of interest in a wide range of areas. It has been widely adopted in industry and has been used to solve a number of non-trivial problems in academia. Putting MapReduce on strong theoretical foundations is crucial in understanding its capabilities. This work links MapReduce to the BSP model of computation, underlining the relevance of BSP to modern parallel algorithm design and deﬁning a subclass of BSP algorithms that can be efficiently implemented in MapReduce.

Connected through hyperedge HE-1 (induced by source paper "connecting mapreduce computations to realistic machine models"):
  with members:
    - "thrill high performance algorithmic distributed batch data processing with c"
    - "communication efficient algorithms for top k selection problems"
    - "sorting searching and simulation in the mapreduce framework"

Connected through hyperedge HE-2 (induced by source paper "a survey on distributed machine learning"):
  with members:
    - "mxnet mpi embedding mpi parallelism in parameter server task model for scaling deep learning"
    - "how to backdoor federated learning"
    - "no peek a survey of private distributed deep learning"
    - "horovod fast and easy distributed deep learning in tensorflow"
    - "poseidon an efficient communication architecture for distributed deep learning on gpu clusters"
    - "scaling deep learning on gpu and knights landing clusters"
    - "revisiting distributed synchronous sgd"
    - "accurate large minibatch sgd training imagenet in 1 hour"

Connected through hyperedge HE-3 (induced by source paper "real time community detection in large social networks on a laptop"):
  with members:
    - "uncovering the small community structure in large networks a local spectral approach"
    - "beyond locality sensitive hashing"
    - "empirical comparison of algorithms for network community detection"
    - "optimal lower bounds for locality sensitive hashing except when q is tiny"
    - "b bit minwise hashing"
    - "lower bounds on locality sensitive hashing"

Connected through hyperedge HE-4 (induced by source paper "on the calm principle for bulk synchronous parallel computation"):
  with members:
    - "blazes coordination analysis for distributed programs"
    - "win move is coordination free sometimes"
    - "shark sql and rich analytics at scale"
    - "relational transducers for declarative networking"

Connected through hyperedge HE-5 (induced by source paper "on the computational complexity of mapreduce"):
  with members:
    - "parallel algorithms for geometric graph problems"
    - "communication steps for parallel query processing"
    - "sorting searching and simulation in the mapreduce framework"

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)