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: "sil an approach for adjusting applications to heterogeneous systems under perturbations"
  Abstract: Scientific applications consist of large and computationally-intensive loops. Dynamic loop scheduling (DLS) techniques are used to load balance the execution of such applications. Load imbalance can be caused by variations in loop iteration execution times due to problem, algorithmic, or systemic characteristics (also, perturbations). The following question motivates this work: "Given an application, a high-performance computing (HPC) system, and both their characteristics and interplay, which DLS technique will achieve improved performance under unpredictable perturbations?" Existing work only considers perturbations caused by variations in the HPC system delivered computational speeds. However, perturbations in available network bandwidth or latency are inevitable on production HPC systems. Simulator in the loop (SiL) is introduced, herein, as a new control-theoretic inspired approach to dynamically select DLS techniques that improve the performance of applications on heterogeneous HPC systems under perturbations. The present work examines the performance of six applications on a heterogeneous system under all above system perturbations. The SiL proof of concept is evaluated using simulation. The performance results confirm the initial hypothesis that no single DLS technique can deliver best performance in all scenarios, while the SiL-based DLS selection delivered improved application performance in most experiments.

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"
    - "experimental verification and analysis of dynamic loop scheduling in scientific applications"
    - "performance reproduction and prediction of selected dynamic loop scheduling experiments"
    - "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"
    - "dynamic loop scheduling using mpi passive target remote memory access"
    - "performance reproduction and prediction of selected dynamic loop scheduling experiments"
    - "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"
    - "dynamic loop scheduling using mpi passive target remote memory access"
    - "performance reproduction and prediction of selected dynamic loop scheduling experiments"
    - "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)