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: "high performance cloud computing a view of scientific applications"
  Abstract: Scientific computing often requires the availability of a massive number of computers for performing large scale experiments. Traditionally, these needs have been addressed by using high-performance computing solutions and installed facilities such as clusters and super computers, which are difficult to setup, maintain, and operate. Cloud computing provides scientists with a completely new model of utilizing the computing infrastructure. Compute resources, storage resources, as well as applications, can be dynamically provisioned (and integrated within the existing infrastructure) on a pay per use basis. These resources can be released when they are no more needed. Such services are often offered within the context of a Service Level Agreement (SLA), which ensure the desired Quality of Service (QoS). Aneka, an enterprise Cloud computing solution, harnesses the power of compute resources by relying on private and public Clouds and delivers to users the desired QoS. Its flexible and service based infrastructure supports multiple programming paradigms that make Aneka address a variety of different scenarios: from finance applications to computational science. As examples of scientific computing in the Cloud, we present a preliminary case study on using Aneka for the classification of gene expression data and the execution of fMRI brain imaging workflow.

Connected through hyperedge HE-1 (induced by source paper "reinforcement learning based autoscaling of workflows in the cloud a survey"):
  with members:
    - "cmi an online multi objective genetic autoscaler for scientific and engineering workflows in cloud infrastructures with unreliable virtual machines"
    - "a disciplined approach to neural network hyper parameters part 1 learning rate batch size momentum and weight decay"
    - "deep learning a critical appraisal"
    - "a comparison of reinforcement learning techniques for fuzzy cloud auto scaling"
    - "automated cloud provisioning on aws using deep reinforcement learning"
    - "dueling network architectures for deep reinforcement learning"
    - "a taxonomy and survey of energy efficient data centers and cloud computing systems"

Connected through hyperedge HE-2 (induced by source paper "snc a cloud service platform for symbolic numeric computation using just in time compilation"):
  with members:
    - "automated derivation of the adjoint of high level transient finite element programs"
    - "introduction to the ginac framework for symbolic computation within the c programming language"

Connected through hyperedge HE-3 (induced by source paper "hpc cloud for scientific and business applications taxonomy vision and research challenges"):
  with members:
    - "in datacenter performance analysis of a tensor processing unit"
    - "about the suitability of clouds in high performance computing"
    - "sla aware interactive workflow assistant for hpc parameter sweeping experiments"
    - "job placement advisor based on turnaround predictions for hpc hybrid clouds"
    - "tensorflow a system for large scale machine learning"
    - "multi cloud resource provisioning with aneka a unified and integrated utilisation of microsoft azure and amazon ec2 instances"
    - "big data computing and clouds"
    - "the anatomy of the grid enabling scalable virtual organizations"

Connected through hyperedge HE-4 (induced by source paper "optical network virtualisation using multitechnology monitoring and sdn enabled optical transceiver"):
  with members:
    - "software defined networking a comprehensive survey"

Connected through hyperedge HE-5 (induced by source paper "job placement advisor based on turnaround predictions for hpc hybrid clouds"):
  with members:
    - "an sla based advisor for placement of hpc jobs on hybrid clouds"

Connected through hyperedge HE-6 (induced by source paper "an sla based advisor for placement of hpc jobs on hybrid clouds"):
  with members:
    - "a self adaptive auto scaling method for scientific applications on hpc environments and clouds"

Connected through hyperedge HE-7 (induced by source paper "a taxonomy and survey on escience as a service in the cloud"):
  with members:
    - "cloud computing and grid computing 360 degree compared"

Connected through hyperedge HE-8 (induced by source paper "trust management in cloud computing a critical review"):
  with members:
    - "survey of trust models in different network domains"

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)