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 "a tight i o lower bound for matrix multiplication"):
  Abstract: A tight lower bound for required I/O when computing an ordinary matrix-matrix multiplication on a processor with two layers of memory is established. Prior work obtained weaker lower bounds by reasoning about the number of segments needed to perform $C:=AB$, for distinct matrices $A$, $B$, and $C$, where each segment is a series of operations involving $M$ reads and writes to and from fast memory, and $M$ is the size of fast memory. A lower bound on the number of segments was then determined by obtaining an upper bound on the number of elementary multiplications performed per segment. This paper follows the same high level approach, but improves the lower bound by (1) transforming algorithms for MMM so that they perform all computation via fused multiply-add instructions (FMAs) and using this to reason about only the cost associated with reading the matrices, and (2) decoupling the per-segment I/O cost from the size of fast memory. For $n \times n$ matrices, the lower bound's leading-order term is $2n^3/\sqrt{M}$. A theoretical algorithm whose leading terms attains this is introduced. To what extent the state-of-the-art Goto's Algorithm attains the lower bound is discussed.

Includes members:
  Member "communication optimal convolutional neural nets":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "flexible communication avoiding matrix multiplication on fpga with high level synthesis")
  Member "a lower bound technique for communication in bsp":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "equivalence classes and conditional hardness in massively parallel computations")
  Member "communication lower bounds for matricized tensor times khatri rao product":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "enabling distributed memory tensor completion in python using new sparse tensor kernels")
  Member "communication lower bounds of bilinear algorithms for symmetric tensor contractions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "pushing the bounds for matrix matrix multiplication")
  Member "communication lower bounds for distributed memory computations":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "equivalence classes and conditional hardness in massively parallel computations")
  Member "communication lower bounds for distributed memory computations":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "equivalence classes and conditional hardness in massively parallel computations")
  Member "minimizing communication in linear algebra":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "communication efficient jaccard similarity for high performance distributed genome comparisons")
  Member "revisiting matrix product on master worker platforms":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "automated derivation of parametric data movement lower bounds for affine programs")

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.CC(Computational Complexity)