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: "a domain specific compiler for linear algebra operations"
  Abstract: We present a prototypical linear algebra compiler that automatically exploits domain-specific knowledge to generate high-performance algorithms. The input to the compiler is a target equation together with knowledge of both the structure of the problem and the properties of the operands. The output is a variety of high-performance algorithms, and the corresponding source code, to solve the target equation. Our approach consists in the decomposition of the input equation into a sequence of library-supported kernels. Since in general such a decomposition is not unique, our compiler returns not one but a number of algorithms. The potential of the compiler is shown by means of its application to a challenging equation arising within the genome-wide association study. As a result, the compiler produces multiple "best" algorithms that outperform the best existing libraries.

Connected through hyperedge HE-1 (induced by source paper "linnea automatic generation of efficient linear algebra programs"):
  with members:
    - "the linear algebra mapping problem"
    - "automatic generation of efficient linear algebra programs"
    - "the generalized matrix chain algorithm"
    - "non linear associative commutative many to one pattern matching with sequence variables"
    - "efficient pattern matching in python"
    - "matchpy a pattern matching library"
    - "sparsity based correction of exponential artifacts"
    - "a parallel implementation of the ensemble kalman filter based on modified cholesky decomposition"

Connected through hyperedge HE-2 (induced by source paper "the linear algebra mapping problem"):
  with members:
    - "automatic generation of efficient linear algebra programs"
    - "clblast a tuned opencl blas library"
    - "the generalized matrix chain algorithm"
    - "image restoration by iterative denoising and backward projections"
    - "recursive algorithms for dense linear algebra the relapack collection"
    - "sparsity based correction of exponential artifacts"
    - "on a natural dynamics for linear programming"
    - "julia a fresh approach to numerical computing"

Connected through hyperedge HE-3 (induced by source paper "automatic generation of efficient linear algebra programs"):
  with members:
    - "the generalized matrix chain algorithm"
    - "non linear associative commutative many to one pattern matching with sequence variables"
    - "efficient pattern matching in python"
    - "image restoration by iterative denoising and backward projections"
    - "matchpy a pattern matching library"
    - "sparsity based correction of exponential artifacts"
    - "a parallel implementation of the ensemble kalman filter based on modified cholesky decomposition"
    - "on a natural dynamics for linear programming"

Connected through hyperedge HE-4 (induced by source paper "the generalized matrix chain algorithm"):
  with members:
    - "non linear associative commutative many to one pattern matching with sequence variables"
    - "deriving correct high performance algorithms"
    - "a dual method for computing power transfer distribution factors"
    - "sparsity based correction of exponential artifacts"
    - "a parallel implementation of the ensemble kalman filter based on modified cholesky decomposition"
    - "consistent discretization and minimization of the l1 norm on manifolds"
    - "the elaps framework experimental linear algebra performance studies"
    - "on a natural dynamics for linear programming"

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)