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: "a parallel framework for reverse search using mts"
  Abstract: We describe mts, which is a generic framework for parallelizing certain types of tree search programs, that (a) provides a single common wrapper containing all of the parallelization, and (b) minimizes the changes needed to the existing single processor legacy code. The mts code was derived from ideas used to develop mplrs, a parallelization of the reverse search vertex enumeration code lrs. The tree search properties required for the use of mts are satisfied by any reverse search algorithm as well as other tree search methods such as backtracking and branch and bound. mts is programmed in C, uses the MPI parallel environment, and can be run on a network of computers. #R##N#As examples we parallelize two simple existing reverse search codes: generating topological orderings and generating spanning trees of a graph. We give computational results comparing the parallel codes with state of the art sequential codes for the same problems.

Connected through hyperedge HE-1 (induced by source paper "mts a light framework for parallelizing tree search codes"):
  with members:
    - "an analysis of budgeted parallel search on conditional galton watson trees"
    - "solving and verifying the boolean pythagorean triples problem via cube and conquer"
    - "mplrs a scalable parallel vertex facet enumeration code"
    - "the shape of the search tree for the maximum clique problem and the implications for parallel branch and bound"

Connected through hyperedge HE-2 (induced by source paper "an analysis of budgeted parallel search on conditional galton watson trees"):
  with members:
    - "mplrs a scalable parallel vertex facet enumeration code"
    - "the shape of the search tree for the maximum clique problem and the implications for parallel branch and bound"

Connected through hyperedge HE-3 (induced by source paper "mplrs a scalable parallel vertex facet enumeration code"):
  with members:
    - "an analysis of budgeted parallel search on conditional galton watson trees"
    - "faster geometric algorithms via dynamic determinant computation"
    - "hordesat a massively parallel portfolio sat solver"
    - "bounds on multiple sensor fusion"
    - "the shape of the search tree for the maximum clique problem and the implications for parallel branch and bound"
    - "the parma polyhedra library toward a complete set of numerical abstractions for the analysis and verification of hardware and software systems"

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.DC(Distributed, Parallel, and Cluster Computing)