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 "hpc ai500 a benchmark suite for hpc ai systems"):
  Abstract: In recent years, with the trend of applying deep learning (DL) in high performance scientific computing, the unique characteristics of emerging DL workloads in HPC raise great challenges in designing, implementing HPC AI systems. The community needs a new yard stick for evaluating the future HPC systems. In this paper, we propose HPC AI500 --- a benchmark suite for evaluating HPC systems that running scientific DL workloads. Covering the most representative scientific fields, each workload from HPC AI500 is based on real-world scientific DL applications. Currently, we choose 14 scientific DL benchmarks from perspectives of application scenarios, data sets, and software stack. We propose a set of metrics for comprehensively evaluating the HPC AI systems, considering both accuracy, performance as well as power and cost. We provide a scalable reference implementation of HPC AI500. HPC AI500 is a part of the open-source AIBench project, the specification and source code are publicly available from \url{this http URL}.

Includes members:
  Member "a modular benchmarking infrastructure for high performance and reproducible deep learning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "practice of streaming and dynamic graphs concepts models systems and parallelism")
  Member "edge aibench towards comprehensive end to end edge computing benchmarking":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "ai oriented medical workload allocation for hierarchical cloud edge device computing")
  Member "automatic chemical design using a data driven continuous representation of molecules":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hierarchical generation of molecular graphs using structural motifs")
  Member "horovod fast and easy distributed deep learning in tensorflow":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "communication optimization strategies for distributed deep learning a survey")
  Member "tbd benchmarking and analyzing deep neural network training":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "aibench an agile domain specific benchmarking methodology and an ai benchmark suite")
  Member "globenet convolutional neural networks for typhoon eye tracking from remote sensing imagery":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "exascale deep learning for climate analytics")
  Member "scaling grpc tensorflow on 512 nodes of cori supercomputer":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "meth a family of high resolution and variable shape image challenges")
  Member "benchmarking state of the art deep learning software tools":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a survey on distributed machine learning")

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.PF(Performance)