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: "p3dfft a framework for parallel computations of fourier transforms in three dimensions"
  Abstract: Fourier and related transforms are a family of algorithms widely employed in diverse areas of computational science, notoriously difficult to scale on high-performance parallel computers with a large number of processing elements (cores). This paper introduces a popular software package called P3DFFT which implements fast Fourier transforms (FFTs) in three dimensions in a highly efficient and scalable way. It overcomes a well-known scalability bottleneck of three-dimensional (3D) FFT implementations by using two-dimensional domain decomposition. Designed for portable performance, P3DFFT achieves excellent timings for a number of systems and problem sizes. On a Cray XT5 system P3DFFT attains 45% efficiency in weak scaling from 128 to 65,536 computational cores. Library features include Fourier and Chebyshev transforms, Fortran and C interfaces, in- and out-of-place transforms, uneven data grids, and single and double precision. P3DFFT is available as open source at http://code.google.com/p/p3dfft/. This pa...

Connected through hyperedge HE-1 (induced by source paper "large scale discrete fourier transform on tpus"):
  with members:
    - "evaluating modern gpu interconnect pcie nvlink nv sli nvswitch and gpudirect"
    - "leveraging the bfloat16 artificial intelligence datatype for higher precision computations"
    - "a flexible framework for parallel multi dimensional dfts"
    - "high performance monte carlo simulation of ising model on tpu clusters"
    - "tensor processing units for financial monte carlo"
    - "in datacenter performance analysis of a tensor processing unit"
    - "a berkeley view of systems challenges for ai"
    - "google s neural machine translation system bridging the gap between human and machine translation"

Connected through hyperedge HE-2 (induced by source paper "croft a scalable three dimensional parallel fast fourier transform fft implementation for high performance clusters"):
  with members:
    - "accfft a library for distributed memory fft on cpu and gpu architectures"

Connected through hyperedge HE-3 (induced by source paper "fluidfft common api c and python for fast fourier transform hpc libraries"):
  with members:
    - "fluidsim modular object oriented python package for high performance cfd simulations"

Connected through hyperedge HE-4 (induced by source paper "fast parallel multidimensional fft using advanced mpi"):
  with members:
    - "high performance python for direct numerical simulations of turbulent flows"
    - "a decomposition method with minimum communication amount for parallelization of multi dimensional ffts"

Connected through hyperedge HE-5 (induced by source paper "hptt a high performance tensor transposition c library"):
  with members:
    - "cutt a high performance tensor transpose library for cuda compatible gpus"
    - "ttc a high performance compiler for tensor transpositions"
    - "design of a high performance gemm like tensor tensor multiplication"
    - "madness a multiresolution adaptive numerical environment for scientific simulation"
    - "ttc a tensor transposition compiler for multiple architectures"
    - "tensorflow large scale machine learning on heterogeneous distributed systems"
    - "fast convolutional nets with fbfft a gpu performance evaluation"

Connected through hyperedge HE-6 (induced by source paper "design of a high performance gemm like tensor tensor multiplication"):
  with members:
    - "hptt a high performance tensor transposition c library"
    - "ttc a high performance compiler for tensor transpositions"
    - "madness a multiresolution adaptive numerical environment for scientific simulation"
    - "ttc a tensor transposition compiler for multiple architectures"
    - "tensor contractions with extended blas kernels on cpu and gpu"
    - "tensorflow large scale machine learning on heterogeneous distributed systems"
    - "fast convolutional nets with fbfft a gpu performance evaluation"
    - "cudnn efficient primitives for deep learning"

Connected through hyperedge HE-7 (induced by source paper "ttc a high performance compiler for tensor transpositions"):
  with members:
    - "hptt a high performance tensor transposition c library"
    - "design of a high performance gemm like tensor tensor multiplication"
    - "madness a multiresolution adaptive numerical environment for scientific simulation"
    - "ttc a tensor transposition compiler for multiple architectures"
    - "tensorflow large scale machine learning on heterogeneous distributed systems"
    - "fast convolutional nets with fbfft a gpu performance evaluation"
    - "cudnn efficient primitives for deep learning"
    - "towards an efficient use of the blas library for multilinear tensor contractions"

Connected through hyperedge HE-8 (induced by source paper "ttc a tensor transposition compiler for multiple architectures"):
  with members:
    - "ttc a high performance compiler for tensor transpositions"
    - "madness a multiresolution adaptive numerical environment for scientific simulation"
    - "tensorflow large scale machine learning on heterogeneous distributed systems"
    - "fast convolutional nets with fbfft a gpu performance evaluation"

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)