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: "task parallel analysis of molecular dynamics trajectories"
  Abstract: Different frameworks for implementing parallel data analytics applications have been proposed by the HPC and Big Data communities. In this paper, we investigate three frameworks: Spark, Dask and RADICAL-Pilot with respect to their ability to support data analytics requirements on HPC resources. We investigate the data analysis requirements of Molecular Dynamics (MD) simulations which are significant consumers of supercomputing cycles, producing immense amounts of data: a typical large-scale MD simulation of physical systems of O(100,000) atoms can produce from O(10) GB to O(1000) GBs of data. We propose and evaluate different approaches for parallelization of a representative set of MD trajectory analysis algorithms, in particular the computation of path similarity and the identification of connected atom. We evaluate Spark, Dask and \rp with respect to the provided abstractions and runtime engine capabilities to support these algorithms. We provide a conceptual basis for comparing and understanding the different frameworks that enable users to select the optimal system for its application. Further, we provide a quantitative performance analysis of the different algorithms across the three frameworks using different high-performance computing resources.

Connected through hyperedge HE-1 (induced by source paper "performance evaluation of big data processing strategies for neuroimaging"):
  with members:
    - "fast and scalable distributed deep convolutional autoencoder for fmri big data analytics"
    - "comparative evaluation of big data systems on scientific image analytics workloads"

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)