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: "memory efficient scheduling of strassen winograd s matrix multiplication algorithm"
  Abstract: We propose several new schedules for Strassen-Winograd's matrix multiplication algorithm, they reduce the extra memory allocation requirements by three different means: by introducing a few pre-additions, by overwriting the input matrices, or by using a first recursive level of classical multiplication. In particular, we show two fully in-place schedules: one having the same number of operations, if the input matrices can be overwritten; the other one, slightly increasing the constant of the leading term of the complexity, if the input matrices are read-only. Many of these schedules have been found by an implementation of an exhaustive search algorithm based on a pebble game.

Connected through hyperedge HE-1 (induced by source paper "improving the space time efficiency of processor oblivious matrix multiplication algorithms"):
  with members:
    - "extending the nested parallel model to the nested dataflow model with provably efficient schedulers"
    - "implementing strassen s algorithm with blis"
    - "a framework for practical parallel fast matrix multiplication"
    - "communication optimal parallel algorithm for strassen s matrix multiplication"
    - "minimizing communication in linear algebra"

Connected through hyperedge HE-2 (induced by source paper "generic reductions for in place polynomial multiplication"):
  with members:
    - "space efficient karatsuba multiplication for multi precision integers"
    - "faster polynomial multiplication over finite fields"
    - "an in place truncated fourier transform and applications to polynomial multiplication"

Connected through hyperedge HE-3 (induced by source paper "matrix multiplication trilinear decompositions apa algorithms and summation"):
  with members:
    - "fast matrix multiplication limitations of the laser method"
    - "powers of tensors and fast matrix multiplication"
    - "better late than never filling a void in the history of fast matrix multiplication and tensor decompositions"
    - "faster algorithms for rectangular matrix multiplication"
    - "all pairs shortest paths using bridging sets and rectangular matrix multiplication"

Connected through hyperedge HE-4 (induced by source paper "elements of design for containers and solutions in the linbox library"):
  with members:
    - "faster arithmetic for number theoretic transforms"
    - "parallel computation of echelon forms"
    - "linbox founding scope allocation parallel building blocks and separate compilation"
    - "exact sparse matrix vector multiplication on gpu s and multicore architectures"

Connected through hyperedge HE-5 (induced by source paper "tiled algorithms for matrix computations on multicore architectures"):
  with members:
    - "communication optimal parallel algorithm for strassen s matrix multiplication"
    - "tiled qr factorization algorithms"
    - "towards an efficient tile matrix inversion of symmetric positive definite matrices on multicore architectures"
    - "a critical path approach to analyzing parallelism of algorithmic variants application to cholesky inversion"
    - "a class of parallel tiled linear algebra algorithms for multicore architectures"

Connected through hyperedge HE-6 (induced by source paper "rank profile revealing gaussian elimination and the cup matrix decomposition"):
  with members:
    - "the m4rie library for dense linear algebra over small fields with even characteristic"

Connected through hyperedge HE-7 (induced by source paper "dense linear algebra over finite fields the fflas and ffpack packages"):
  with members:
    - "q adic transform revisited"
    - "efficient computation of the characteristic polynomial"
    - "fast computation of moore penrose inverse matrices"

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.MS(Mathematical Software)