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: "computing petaflops over terabytes of data the case of genome wide association studies"
  Abstract: In many scientific and engineering applications, one has to solve not one but a sequence of instances of the same problem. Often times, the problems in the sequence are linked in a way that allows intermediate results to be reused. A characteristic example for this class of applications is given by the Genome-Wide Association Studies (GWAS), a widely spread tool in computational biology. GWAS entails the solution of up to trillions ($10^{12}$) of correlated generalized least-squares problems, posing a daunting challenge: the performance of petaflops ($10^{15}$ floating-point operations) over terabytes of data. #R##N#In this paper, we design an algorithm for performing GWAS on multi-core architectures. This is accomplished in three steps. First, we show how to exploit the relation among successive problems, thus reducing the overall computational complexity. Then, through an analysis of the required data transfers, we identify how to eliminate any overhead due to input/output operations. Finally, we study how to decompose computation into tasks to be distributed among the available cores, to attain high performance and scalability. With our algorithm, a GWAS that currently requires the use of a supercomputer may now be performed in matter of hours on a single multi-core node. #R##N#The discussion centers around the methodology to develop the algorithm rather than the specific application. We believe the paper contributes valuable guidelines of general applicability for computational scientists on how to develop and optimize numerical algorithms.

Connected through hyperedge HE-1 (induced by source paper "the linear algebra mapping problem"):
  with members:
    - "automatic generation of efficient linear algebra programs"
    - "clblast a tuned opencl blas library"
    - "the generalized matrix chain algorithm"
    - "image restoration by iterative denoising and backward projections"
    - "recursive algorithms for dense linear algebra the relapack collection"
    - "sparsity based correction of exponential artifacts"
    - "on a natural dynamics for linear programming"
    - "julia a fresh approach to numerical computing"

Connected through hyperedge HE-2 (induced by source paper "accelerating the computation of flapw methods on heterogeneous architectures"):
  with members:
    - "billion scale similarity search with gpus"
    - "high performance generation of the hamiltonian and overlap matrices in flapw methods"
    - "hybrid cpu gpu generation of the hamiltonian and overlap matrices in flapw methods"
    - "blasx a high performance level 3 blas library for heterogeneous multi gpu computing"

Connected through hyperedge HE-3 (induced by source paper "the elaps framework experimental linear algebra performance studies"):
  with members:
    - "on the performance prediction of blas based tensor contractions"
    - "performance modeling for dense linear algebra"
    - "solving sequences of generalized least squares problems on multi threaded architectures"

Connected through hyperedge HE-4 (induced by source paper "large scale linear regression development of high performance routines"):
  with members:
    - "knowledge based automatic generation of partitioned matrix expressions"
    - "solving sequences of generalized least squares problems on multi threaded architectures"

Connected through hyperedge HE-5 (induced by source paper "streaming data from hdd to gpus for sustained peak performance"):
  with members:
    - "solving sequences of generalized least squares problems on multi threaded architectures"

Connected through hyperedge HE-6 (induced by source paper "algorithms for large scale whole genome association analysis"):
  with members:
    - "solving sequences of generalized least squares problems on multi threaded architectures"

Connected through hyperedge HE-7 (induced by source paper "application tailored linear algebra algorithms a search based approach"):
  with members:
    - "performance modeling for dense linear algebra"
    - "high throughput genome wide association analysis for single and multiple phenotypes"
    - "dolfin automated finite element computing"

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)