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 "numerical analysis of the maximal attainable accuracy in communication hiding pipelined conjugate gradient methods"):
  Abstract: Krylov subspace methods are widely known as efficient algebraic methods for solving large scale linear systems. However, on massively parallel hardware the performance of these methods is typically limited by communication latency rather than floating point performance. With HPC hardware advancing towards the exascale regime the gap between computation and communication keeps steadily increasing, imposing the need for scalable alternatives to traditional Krylov subspace methods. One such approach are the so-called pipelined Krylov subspace methods, which reduce the number of global synchronization points and overlap global communication latency with local arithmetic operations, thus hiding the global reduction phases behind useful computations. To obtain this overlap the traditional Krylov subspace algorithm is reformulated by introducing a number of auxiliary vector quantities, which are computed using additional recurrence relations. Although pipelined Krylov subspace methods are equivalent to traditional Krylov subspace methods in exact arithmetic, local rounding errors induced by the multi-term recurrence relations in finite precision may in practice affect convergence significantly. This numerical stability study aims to characterize the effect of local rounding errors on attainable accuracy in various pipelined versions of the popular Conjugate Gradient method. Expressions for the gaps between the true and recursively computed variables that are used to update the search directions in the different CG variants are derived. Furthermore, it is shown how these results can be used to analyze and correct the effect of local rounding error propagation on the maximal attainable accuracy of pipelined CG methods. The analysis in this work is supplemented by numerical experiments that demonstrate the numerical behavior of the pipelined CG methods.

Includes members:
  Member "the communication hiding conjugate gradient method with deep pipelines":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "scalable resilience against node failures for communication hiding preconditioned conjugate gradient and conjugate residual methods")
  Member "a stochastic performance model for pipelined krylov methods":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "comparative study of finite element methods using the time accuracy size tas spectrum analysis")

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.NA(Numerical Analysis)