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: "performance reproduction and prediction of selected dynamic loop scheduling experiments"
  Abstract: Scientific applications are complex, large, and often exhibit irregular and stochastic behavior. The use of efficient loop scheduling techniques in computationally-intensive applications is crucial for improving their performance on high-performance computing (HPC) platforms. A number of dynamic loop scheduling (DLS) techniques have been proposed between the late 1980s and early 2000s, and efficiently used in scientific applications. In most cases, the computing systems on which they have been tested and validated are no longer available. This work is concerned with the minimization of the sources of uncertainty in the implementation of DLS techniques to avoid unnecessary influences on the performance of scientific applications. Therefore, it is important to ensure that the DLS techniques employed in scientific applications today adhere to their original design goals and specifications. The goal of this work is to attain and increase the trust in the implementation of DLS techniques in present studies. To achieve this goal, the performance of a selection of scheduling experiments from the 1992 original work that introduced factoring is reproduced and predicted via both, simulative and native experimentation. The experiments show that the simulation reproduces the performance achieved on the past computing platform and accurately predicts the performance achieved on the present computing platform. The performance reproduction and prediction confirm that the present implementation of the DLS techniques considered both, in simulation and natively, adheres to their original description. The results confirm the hypothesis that reproducing experiments of identical scheduling scenarios on past and modern hardware leads to an entirely different behavior from expected.

Connected through hyperedge HE-1 (induced by source paper "an approach for realistically simulating the performance of scientific applications on high performance computing systems"):
  with members:
    - "openmp loop scheduling revisited making a case for more schedules"
    - "sil an approach for adjusting applications to heterogeneous systems under perturbations"
    - "experimental verification and analysis of dynamic loop scheduling in scientific applications"
    - "efficient generation of parallel spin images using dynamic loop scheduling"
    - "exploring the relation between two levels of scheduling using a novel simulation approach"

Connected through hyperedge HE-2 (induced by source paper "online research report rdlb a novel approach for robust dynamic load balancing of scientific applications with parallel independent tasks"):
  with members:
    - "openmp loop scheduling revisited making a case for more schedules"
    - "sil an approach for adjusting applications to heterogeneous systems under perturbations"
    - "dynamic loop scheduling using mpi passive target remote memory access"
    - "efficient generation of parallel spin images using dynamic loop scheduling"

Connected through hyperedge HE-3 (induced by source paper "rdlb a novel approach for robust dynamic load balancing of scientific applications with parallel independent tasks"):
  with members:
    - "openmp loop scheduling revisited making a case for more schedules"
    - "sil an approach for adjusting applications to heterogeneous systems under perturbations"
    - "dynamic loop scheduling using mpi passive target remote memory access"
    - "efficient generation of parallel spin images using dynamic loop scheduling"

Connected through hyperedge HE-4 (induced by source paper "simas a simulation assisted approach for the scheduling algorithm selection under perturbations"):
  with members:
    - "an approach for realistically simulating the performance of scientific applications on high performance computing systems"
    - "experimental verification and analysis of dynamic loop scheduling in scientific applications"
    - "the importance and need for system monitoring and analysis in hpc operations and research"
    - "efficient generation of parallel spin images using dynamic loop scheduling"

Connected through hyperedge HE-5 (induced by source paper "sil an approach for adjusting applications to heterogeneous systems under perturbations"):
  with members:
    - "experimental verification and analysis of dynamic loop scheduling in scientific applications"
    - "the importance and need for system monitoring and analysis in hpc operations and research"
    - "efficient generation of parallel spin images using dynamic loop scheduling"

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)