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: "orthogononalization on a general purpose graphics processing unit with double double and quad double arithmetic"
  Abstract: Our problem is to accurately solve linear systems on a general purpose graphics processing unit with double double and quad double arithmetic. The linear systems originate from the application of Newton's method on polynomial systems. Newton's method is applied as a corrector in a path following method, so the linear systems are solved in sequence and not simultaneously. One solution path may require the solution of thousands of linear systems. In previous work we reported good speedups with our implementation to evaluate and differentiate polynomial systems on the NVIDIA Tesla C2050. Although the cost of evaluation and differentiation often dominates the cost of linear system solving in Newton's method, because of the limited bandwidth of the communication between CPU and GPU, we cannot afford to send the linear system to the CPU for solving during path tracking. #R##N#Because of large degrees, the Jacobian matrix may contain extreme values, requiring extended precision, leading to a significant overhead. This overhead of multiprecision arithmetic is our main motivation to develop a massively parallel algorithm. To allow overdetermined linear systems we solve linear systems in the least squares sense, computing the QR decomposition of the matrix by the modified Gram-Schmidt algorithm. We describe our implementation of the modified Gram-Schmidt orthogonalization method for the NVIDIA Tesla C2050, using double double and quad double arithmetic. Our experimental results show that the achieved speedups are sufficiently high to compensate for the overhead of one extra level of precision.

Connected through hyperedge HE-1 (induced by source paper "accelerating polynomial homotopy continuation on a graphics processing unit with double double and quad double arithmetic"):
  with members:
    - "solving polynomial systems in the cloud with polynomial homotopy continuation"
    - "gpu acceleration of newton s method for large systems of polynomial equations in double double and quad double arithmetic"
    - "modernizing phcpack through phcpy"
    - "computing puiseux series for algebraic surfaces"
    - "evaluating polynomials in several variables and their derivatives on a gpu computing processor"

Connected through hyperedge HE-2 (induced by source paper "tracking many solution paths of a polynomial homotopy on a graphics processing unit"):
  with members:
    - "accelerating polynomial homotopy continuation on a graphics processing unit with double double and quad double arithmetic"
    - "gpu acceleration of newton s method for large systems of polynomial equations in double double and quad double arithmetic"
    - "modernizing phcpack through phcpy"
    - "evaluating polynomials in several variables and their derivatives on a gpu computing processor"

Connected through hyperedge HE-3 (induced by source paper "gpu acceleration of newton s method for large systems of polynomial equations in double double and quad double arithmetic"):
  with members:
    - "evaluating polynomials in several variables and their derivatives on a gpu computing processor"

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)