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 "communication avoiding cholesky qr2 for rectangular matrices"):
  Abstract: The need for scalable algorithms to solve least squares and eigenvalue problems is becoming increasingly important given the rising complexity of modern machines. We address this concern by presenting a new scalable QR factorization algorithm intended to accelerate these problems for rectangular matrices. Our contribution is a communication-avoiding distributed-memory parallelization of an existing Cholesky-based QR factorization algorithm called CholeskyQR2. Our algorithm exploits a tunable processor grid able to interpolate between one and three dimensions, resulting in tradeoffs in the asymptotic costs of synchronization, horizontal bandwidth, flop count, and memory footprint. It improves the communication cost complexity with respect to state-of-the-art parallel QR implementations by $\Theta(P^{\frac{1}{6}})$. Further, we provide implementation details and performance results on Blue Waters supercomputer. We show that the costs attained are asymptotically equivalent to other communication-avoiding QR factorization algorithms and demonstrate that our algorithm is efficient in practice.

Includes members:
  Member "a 3d parallel algorithm for qr decomposition":
    also connected through other hyperedges:
      (none)
  Member "communication avoiding parallel algorithms for solving triangular systems of linear equations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "straggler resilient and communication efficient distributed iterative linear solver")
  Member "a communication avoiding parallel algorithm for the symmetric eigenvalue problem":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a 3d parallel algorithm for qr decomposition")

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)