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 performance tensor contraction without transposition"):
  Abstract: Tensor computations--in particular tensor contraction (TC)--are important kernels in many scientific computing applications. Due to the fundamental similarity of TC to matrix multiplication (MM) and to the availability of optimized implementations such as the BLAS, tensor operations have traditionally been implemented in terms of BLAS operations, incurring both a performance and a storage overhead. Instead, we implement TC using the flexible BLIS framework, which allows for transposition (reshaping) of the tensor to be fused with internal partitioning and packing operations, requiring no explicit transposition operations or additional workspace. This implementation, TBLIS, achieves performance approaching that of MM, and in some cases considerably higher than that of traditional TC. Our implementation supports multithreading using an approach identical to that used for MM in BLIS, with similar performance characteristics. The complexity of managing tensor-to-matrix transformations is also handled automatically in our approach, greatly simplifying its use in scientific applications.

Includes members:
  Member "ttc a high performance compiler for tensor transpositions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hptt a high performance tensor transposition c library")
  Member "design of a high performance gemm like tensor tensor multiplication":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "yet another tensor toolbox for discontinuous galerkin methods and other applications")
  Member "task based algorithm for matrix multiplication a step towards block sparse tensor computing":
    also connected through other hyperedges:
      (none)
  Member "scalable task based algorithm for multiplication of block rank sparse matrices":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "mesh tensorflow deep learning for supercomputers")
  Member "on the performance prediction of blas based tensor contractions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "tensor contractions with extended blas kernels on cpu and gpu")
  Member "towards an efficient use of the blas library for multilinear tensor contractions":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "yet another tensor toolbox for discontinuous galerkin methods and other applications")
  Member "the numpy array a structure for efficient numerical computation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a deep unsupervised feature learning spiking neural network with binarized classification layers for emnist classification")

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.MS(Mathematical Software)