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 "scalable resilience against node failures for communication hiding preconditioned conjugate gradient and conjugate residual methods"):
  Abstract: The observed and expected continued growth in the number of nodes in large-scale parallel computers gives rise to two major challenges: global communication operations are becoming major bottlenecks due to their limited scalability, and the likelihood of node failures is increasing. We study an approach for addressing these challenges in the context of solving large sparse linear systems. In particular, we focus on the pipelined preconditioned conjugate gradient (PPCG) method, which has been shown to successfully deal with the first of these challenges. In this paper, we address the second challenge. We present extensions to the PPCG solver and two of its variants which make them resilient against the failure of a compute node while fully preserving their communication-hiding properties and thus their scalability. The basic idea is to efficiently communicate a few redundant copies of local vector elements to neighboring nodes with very little overhead. In case a node fails, these redundant copies are gathered at a replacement node, which can then accurately reconstruct the lost parts of the solver's state. After that, the parallel solver can continue as in the failure-free scenario. Experimental evaluations of our approach illustrate on average very low runtime overheads compared to the standard non-resilient algorithms. This shows that scalable algorithmic resilience can be achieved at low extra cost.

Includes members:
  Member "improving strong scaling of the conjugate gradient method for solving large linear systems using global reduction pipelining":
    also connected through other hyperedges:
      (none)
  Member "how to make the preconditioned conjugate gradient method resilient against multiple node failures":
    also connected through other hyperedges:
      (none)
  Member "numerically stable recurrence relations for the communication hiding pipelined conjugate gradient method":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "improving strong scaling of the conjugate gradient method for solving large linear systems using global reduction pipelining")
  Member "the communication hiding conjugate gradient method with deep pipelines":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "improving strong scaling of the conjugate gradient method for solving large linear systems using global reduction pipelining")
  Member "numerical analysis of the maximal attainable accuracy in communication hiding pipelined conjugate gradient methods":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "new communication hiding conjugate gradient variants")
  Member "the adaptive s step conjugate gradient method":
    also connected through other hyperedges:
      (none)
  Member "numerically stable variants of the communication hiding pipelined conjugate gradients algorithm for the parallel solution of large scale symmetric linear systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "new communication hiding conjugate gradient variants")
  Member "a backward forward recovery approach for the preconditioned conjugate gradient method":
    also connected through other hyperedges:
      (none)

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.DC(Distributed, Parallel, and Cluster Computing)