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 "a versatile software systolic execution model for gpu memory bound kernels"):
  Abstract: This paper proposes a versatile high-performance execution model, inspired by systolic arrays, for memory-bound regular kernels running on CUDA-enabled GPUs. We formulate a systolic model that shifts partial sums by CUDA warp primitives for the computation. We also employ register files as a cache resource in order to operate the entire model efficiently. We demonstrate the effectiveness and versatility of the proposed model for a wide variety of stencil kernels that appear commonly in HPC, and also convolution kernels (increasingly important in deep learning workloads). Our algorithm outperforms the top reported state-of-the-art stencil implementations, including implementations with sophisticated temporal and spatial blocking techniques, on the two latest Nvidia architectures: Tesla V100 and P100. For 2D convolution of general filter sizes and shapes, our algorithm is on average 2.5× faster than Nvidia's NPP on V100 and P100 GPUs.

Includes members:
  Member "regdem increasing gpu performance via shared memory register spilling":
    also connected through other hyperedges:
      (none)
  Member "stateful dataflow multigraphs a data centric model for performance portability on heterogeneous architectures":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hlslib software engineering for hardware design")
  Member "dissecting the nvidia turing t4 gpu via microbenchmarking":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "gpu tensor cores for fast arithmetic reductions")
  Member "combined spatial and temporal blocking for high performance stencil computation on fpgas using opencl":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an5d automated stencil framework for high degree temporal blocking on gpus")
  Member "dissecting the nvidia volta gpu architecture via microbenchmarking":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "gpu tensor cores for fast arithmetic reductions")
  Member "in datacenter performance analysis of a tensor processing unit":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "train large then compress rethinking model size for efficient training and inference of transformers")
  Member "multicore optimized wavefront diamond blocking for optimizing stencil updates":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "collecting and presenting reproducible intranode stencil performance inspect")
  Member "cudnn efficient primitives for deep learning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "searching for winograd aware quantized networks")

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.DC(Distributed, Parallel, and Cluster Computing)