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: "mpi windows on storage for hpc applications"
  Abstract: Upcoming HPC clusters will feature hybrid memories and storage devices per compute node. In this work, we propose to use the MPI one-sided communication model and MPI windows as unique interface for programming memory and storage. We describe the design and implementation of MPI storage windows, and present its benefits for out-of-core execution, parallel I/O and fault-tolerance. In addition, we explore the integration of heterogeneous window allocations, where memory and storage share a unified virtual address space. When performing large, irregular memory operations, we verify that MPI windows on local storage incurs a 55% performance penalty on average. When using a Lustre parallel file system, asymmetric performance is observed with over 90% degradation in writing operations. Nonetheless, experimental results of a Distributed Hash Table, the HACC I/O kernel mini-application, and a novel MapReduce implementation based on the use of MPI one-sided communication, indicate that the overall penalty of MPI windows on storage can be negligible in most cases in real-world applications.

Connected through hyperedge HE-1 (induced by source paper "sage percipient storage for exascale data centric computing"):
  with members:
    - "preparing hpc applications for the exascale era a decoupling strategy"
    - "mpi streams for hpc applications"
    - "savu a python based mpi framework for simultaneous processing of multiple n dimensional large tomography datasets"
    - "exploring application performance on emerging hybrid memory supercomputers"
    - "enabling highly scalable remote memory access programming with mpi 3 one sided"

Connected through hyperedge HE-2 (induced by source paper "umap enabling application driven optimizations for page management"):
  with members:
    - "system evaluation of the intel optane byte addressable nvm"
    - "sage percipient storage for exascale data centric computing"

Connected through hyperedge HE-3 (induced by source paper "exploring scientific application performance using large scale object storage"):
  with members:
    - "sage percipient storage for exascale data centric computing"
    - "the sage project a storage centric approach for exascale computing"
    - "daos for extreme scale systems in scientific applications"
    - "exploring the performance benefit of hybrid memory system on hpc environments"
    - "exploring application performance on emerging hybrid memory supercomputers"

Connected through hyperedge HE-4 (induced by source paper "the sage project a storage centric approach for exascale computing"):
  with members:
    - "preparing hpc applications for the exascale era a decoupling strategy"
    - "exploring the performance benefit of hybrid memory system on hpc environments"
    - "extending message passing interface windows to storage"
    - "savu a python based mpi framework for simultaneous processing of multiple n dimensional large tomography datasets"

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)