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 "multiscale computing in the exascale era"):
  Abstract: We expect that multiscale simulations will be one of the main high performance computing workloads in the exascale era. We propose multiscale computing patterns as a generic vehicle to realise load balanced, fault tolerant and energy aware high performance multiscale computing. Multiscale computing patterns should lead to a separation of concerns, whereby application developers can compose multiscale models and execute multiscale simulations, while pattern software realises optimized, fault tolerant and energy aware multiscale computing. We introduce three multiscale computing patterns, present an example of the extreme scaling pattern, and discuss our vision of how this may shape multiscale computing in the exascale era.

Includes members:
  Member "exploiting data representation for fault tolerance":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multi objective optimization for size and resilience of spiking neural networks")
  Member "fabsim facilitating computational research through automation on large scale and distributed e infrastructures":
    also connected through other hyperedges:
      (none)
  Member "an automated multiscale ensemble simulation approach for vascular blood flow":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fabsim facilitating computational research through automation on large scale and distributed e infrastructures")
  Member "flexible composition and execution of high performance high fidelity multiscale biomedical simulations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deepdownscale a deep learning strategy for high resolution weather forecast")
  Member "petascale turbulence simulation using a highly parallel fast multipole method on gpus":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "fast multipole networks")
  Member "survey of multiscale and multiphysics applications and communities":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fabsim facilitating computational research through automation on large scale and distributed e infrastructures")

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)