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: "communication lower bounds for distributed memory computations"
  Abstract: We give lower bounds on the communication complexity required to solve several computational problems in a distributed-memory parallel machine, namely standard matrix multiplication, stencil computations, comparison sorting, and the Fast Fourier Transform. We revisit the assumptions under which preceding results were derived and provide new lower bounds which use much weaker and appropriate hypotheses. Our bounds rely on a mild assumption on work distribution, and strengthen previous results which require either the computation to be balanced among the processors, or specific initial distributions of the input data, or an upper bound on the size of processors' local memories.

Connected through hyperedge HE-1 (induced by source paper "equivalence classes and conditional hardness in massively parallel computations"):
  with members:
    - "walking randomly massively and efficiently"
    - "log diameter rounds algorithms for 2 vertex and 2 edge connectivity"
    - "dynamic algorithms for the massively parallel computation model"
    - "a conditional lower bound on graph connectivity in mapreduce"
    - "efficient circuit simulation in mapreduce"
    - "exponentially faster massively parallel maximal matching"
    - "parallel batch dynamic graphs algorithms and lower bounds"
    - "massively parallel algorithms for finding well connected components in sparse graphs"

Connected through hyperedge HE-2 (induced by source paper "flexible communication avoiding matrix multiplication on fpga with high level synthesis"):
  with members:
    - "red blue pebbling revisited near optimal parallel matrix matrix multiplication"
    - "hlslib software engineering for hardware design"
    - "demystifying parallel and distributed deep learning an in depth concurrency analysis"
    - "communication optimal convolutional neural nets"
    - "integrated model batch and domain parallelism in training neural networks"
    - "communication lower bounds for distributed memory computations"
    - "hitting the memory wall implications of the obvious"

Connected through hyperedge HE-3 (induced by source paper "the i o complexity of hybrid algorithms for square matrix multiplication"):
  with members:
    - "the i o complexity of strassen s matrix multiplication with recomputation"
    - "powers of tensors and fast matrix multiplication"
    - "communication lower bounds for distributed memory computations"
    - "the input output complexity of sparse matrix multiplication"
    - "graph expansion analysis for communication costs of fast rectangular matrix multiplication"
    - "minimizing communication in linear algebra"
    - "communication optimal parallel and sequential cholesky decomposition"

Connected through hyperedge HE-4 (induced by source paper "on the i o complexity of hybrid algorithms for integer multiplication"):
  with members:
    - "faster integer multiplication using short lattice vectors"
    - "the i o complexity of strassen s matrix multiplication with recomputation"
    - "fast integer multiplication using generalized fermat primes"
    - "communication lower bounds for distributed memory computations"
    - "even faster integer multiplication"

Connected through hyperedge HE-5 (induced by source paper "a tight i o lower bound for matrix multiplication"):
  with members:
    - "communication optimal convolutional neural nets"
    - "a lower bound technique for communication in bsp"
    - "communication lower bounds for matricized tensor times khatri rao product"
    - "communication lower bounds of bilinear algorithms for symmetric tensor contractions"
    - "communication lower bounds for distributed memory computations"
    - "minimizing communication in linear algebra"
    - "revisiting matrix product on master worker platforms"

Connected through hyperedge HE-6 (induced by source paper "pushing the bounds for matrix matrix multiplication"):
  with members:
    - "a lower bound technique for communication in bsp"
    - "communication lower bounds for matricized tensor times khatri rao product"
    - "communication lower bounds of bilinear algorithms for symmetric tensor contractions"
    - "communication lower bounds for distributed memory computations"
    - "minimizing communication in linear algebra"
    - "revisiting matrix product on master worker platforms"

Connected through hyperedge HE-7 (induced by source paper "a lower bound technique for communication in bsp"):
  with members:
    - "resource oblivious sorting on multicores"
    - "efficient algorithms with asymmetric read and write costs"
    - "communication lower bounds for distributed memory computations"
    - "network oblivious algorithms"
    - "minimizing communication in linear algebra"

Connected through hyperedge HE-8 (induced by source paper "the i o complexity of strassen s matrix multiplication with recomputation"):
  with members:
    - "powers of tensors and fast matrix multiplication"
    - "communication lower bounds for distributed memory computations"
    - "the input output complexity of sparse matrix multiplication"
    - "graph expansion analysis for communication costs of fast rectangular matrix multiplication"
    - "faster algorithms for rectangular matrix multiplication"
    - "communication optimal parallel algorithm for strassen s matrix multiplication"
    - "minimizing communication in linear algebra"
    - "communication optimal parallel and sequential cholesky decomposition"

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)