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: "numerically stable variants of the communication hiding pipelined conjugate gradients algorithm for the parallel solution of large scale symmetric linear systems"
  Abstract: By reducing the number of global synchronization bottlenecks per iteration and hiding communication behind useful computational work, pipelined Krylov subspace methods achieve significantly improved parallel scalability on present-day HPC hardware. However, this typically comes at the cost of a reduced maximal attainable accuracy. This paper presents and compares several stabilized versions of the communication-hiding pipelined Conjugate Gradients method. The main novel contribution of this work is the reformulation of the multi-term recurrence pipelined CG algorithm by introducing shifts in the recursions for specific auxiliary variables. These shifts reduce the amplification of local rounding errors on the residual. The stability analysis presented in this work provides a rigorous method for selection of the optimal shift value in practice. It is shown that, given a proper choice for the shift parameter, the resulting shifted pipelined CG algorithm restores the attainable accuracy and displays nearly identical robustness to local rounding error propagation compared to classical CG. Numerical results on a variety of SPD benchmark problems compare different stabilization techniques for the pipelined CG algorithm, showing that the shifted pipelined CG algorithm is able to attain a high accuracy while displaying excellent parallel performance.

Connected through hyperedge HE-1 (induced by source paper "scalable resilience against node failures for communication hiding preconditioned conjugate gradient and conjugate residual methods"):
  with members:
    - "improving strong scaling of the conjugate gradient method for solving large linear systems using global reduction pipelining"
    - "how to make the preconditioned conjugate gradient method resilient against multiple node failures"
    - "numerically stable recurrence relations for the communication hiding pipelined conjugate gradient method"
    - "the communication hiding conjugate gradient method with deep pipelines"
    - "numerical analysis of the maximal attainable accuracy in communication hiding pipelined conjugate gradient methods"
    - "the adaptive s step conjugate gradient method"
    - "a backward forward recovery approach for the preconditioned conjugate gradient method"

Connected through hyperedge HE-2 (induced by source paper "new communication hiding conjugate gradient variants"):
  with members:
    - "numerically stable recurrence relations for the communication hiding pipelined conjugate gradient method"
    - "the communication hiding conjugate gradient method with deep pipelines"
    - "numerical analysis of the maximal attainable accuracy in communication hiding pipelined conjugate gradient methods"

Connected through hyperedge HE-3 (induced by source paper "predict and recompute conjugate gradient variants"):
  with members:
    - "numerically stable recurrence relations for the communication hiding pipelined conjugate gradient method"

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.NA(Numerical Analysis)