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: "solving sequences of generalized least squares problems on multi threaded architectures"
  Abstract: Generalized linear mixed-effects models in the context of genome-wide association studies (GWAS) represent a formidable computational challenge: the solution of millions of correlated generalized least-squares problems, and the processing of terabytes of data. We present high performance in-core and out-of-core shared-memory algorithms for GWAS: By taking advantage of domain-specific knowledge, exploiting multi-core parallelism, and handling data efficiently, our algorithms attain unequalled performance. When compared to GenABEL, one of the most widely used libraries for GWAS, on a 12-core processor we obtain 50-fold speedups. As a consequence, our routines enable genome studies of unprecedented size.

Connected through hyperedge HE-1 (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"
    - "computing petaflops over terabytes of data the case of genome wide association studies"

Connected through hyperedge HE-2 (induced by source paper "large scale linear regression development of high performance routines"):
  with members:
    - "knowledge based automatic generation of partitioned matrix expressions"
    - "computing petaflops over terabytes of data the case of genome wide association studies"

Connected through hyperedge HE-3 (induced by source paper "streaming data from hdd to gpus for sustained peak performance"):
  with members:
    - "computing petaflops over terabytes of data the case of genome wide association studies"

Connected through hyperedge HE-4 (induced by source paper "algorithms for large scale whole genome association analysis"):
  with members:
    - "computing petaflops over terabytes of data the case of genome wide association studies"

Connected through hyperedge HE-5 (induced by source paper "computing petaflops over terabytes of data the case of genome wide association studies"):
  with members:
    - "algorithms for large scale whole genome association analysis"

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)