human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "an approach for realistically simulating the performance of scientific applications on high performance computing systems"):
  Abstract: Scientific applications often contain large, computationally-intensive, and irregular parallel loops or tasks that exhibit stochastic characteristics. Applications may suffer from load imbalance during their execution on high-performance computing (HPC) systems due to such characteristics. Dynamic loop self-scheduling (DLS) techniques are instrumental in improving the performance of scientific applications on HPC systems via load balancing. Selecting a DLS technique that results in the best performance for different problems and system sizes requires a large number of exploratory experiments. A theoretical model that can be used to predict the scheduling technique that yields the best performance for a given problem and system has not yet been identified. Therefore, simulation is the most appropriate approach for conducting such exploratory experiments with reasonable costs. This work devises an approach to realistically simulate computationally-intensive scientific applications that employ DLS and execute on HPC systems. Several approaches to represent the application tasks (or loop iterations) are compared to establish their influence on the simulative application performance. A novel simulation strategy is introduced, which transforms a native application code into a simulative code. The native and simulative performance of two computationally-intensive scientific applications are compared to evaluate the realism of the proposed simulation approach. The comparison of the performance characteristics extracted from the native and simulative performance shows that the proposed simulation approach fully captured most of the performance characteristics of interest. This work shows and establishes the importance of simulations that realistically predict the performance of DLS techniques for different applications and system configurations.

Includes members:
  Member "openmp loop scheduling revisited making a case for more schedules":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "online research report rdlb a novel approach for robust dynamic load balancing of scientific applications with parallel independent tasks")
  Member "sil an approach for adjusting applications to heterogeneous systems under perturbations":
    also connected through other hyperedges:
      - 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")
  Member "experimental verification and analysis of dynamic loop scheduling in scientific applications":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "simas a simulation assisted approach for the scheduling algorithm selection under perturbations")
  Member "performance reproduction and prediction of selected dynamic loop scheduling experiments":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "online research report rdlb a novel approach for robust dynamic load balancing of scientific applications with parallel independent tasks")
  Member "efficient generation of parallel spin images using dynamic loop scheduling":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "online research report rdlb a novel approach for robust dynamic load balancing of scientific applications with parallel independent tasks")
  Member "exploring the relation between two levels of scheduling using a novel simulation approach":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "two level dynamic load balancing for high performance scientific applications")

Question: Please tell me which class the source paper 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)