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 "pasta a parallel sparse tensor algorithm benchmark suite"):
  Abstract: Tensor methods have gained increasingly attention from various applications, including machine learning, quantum chemistry, healthcare analytics, social network analysis, data mining, and signal processing, to name a few. Sparse tensors and their algorithms become critical to further improve the performance of these methods and enhance the interpretability of their output. This work presents a sparse tensor algorithm benchmark suite (PASTA) for single- and multi-core CPUs. To the best of our knowledge, this is the first benchmark suite for sparse tensor world. PASTA targets on: 1) helping application users to evaluate different computer systems using its representative computational workloads; 2) providing insights to better utilize existed computer architecture and systems and inspiration for the future design. This benchmark suite is publicly released this https URL.

Includes members:
  Member "load balanced sparse mttkrp on gpus":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a unified iteration space transformation framework for sparse and dense tensor algebra")
  Member "tensor train decomposition on tensorflow t3f":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "lossless compression for 3dcnns based on tensor train decomposition")
  Member "a practical randomized cp tensor decomposition":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "robust deep networks with randomized tensor regression layers")
  Member "software for sparse tensor decomposition on emerging computing architectures":
    also connected through other hyperedges:
      (none)
  Member "spartan scalable parafac2 for large sparse data":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a parallel sparse tensor benchmark suite on cpus and gpus")
  Member "tensor regression meets gaussian processes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "multiresolution tensor learning for efficient and interpretable spatial analysis")
  Member "tensor computation a new framework for high dimensional problems in eda":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "prediction of multi dimensional spatial variation data via bayesian tensor completion")
  Member "a unified optimization approach for sparse tensor operations on gpus":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a parallel sparse tensor benchmark suite on cpus and gpus")

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)