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 systematic survey of general sparse matrix matrix multiplication"):
  Abstract: SpGEMM (General Sparse Matrix-Matrix Multiplication) has attracted much attention from researchers in fields of multigrid methods and graph analysis. Many optimization techniques have been developed for certain application fields and computing architecture over the decades. The objective of this paper is to provide a structured and comprehensive overview of the research on SpGEMM. Existing optimization techniques have been grouped into different categories based on their target problems and architectures. Covered topics include SpGEMM applications, size prediction of result matrix, matrix partitioning and load balancing, result accumulating, and target architecture-oriented optimization. The rationales of different algorithms in each category are analyzed, and a wide range of SpGEMM algorithms are summarized. This survey sufficiently reveals the latest progress and research status of SpGEMM optimization from 1977 to 2019. More specifically, an experimentally comparative study of existing implementations on CPU and GPU is presented. Based on our findings, we highlight future research directions and how future studies can leverage our findings to encourage better design and implementation.

Includes members:
  Member "high performance sparse matrix matrix products on intel knl and multicore architectures":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "fast sparse convnets")
  Member "sparse matrix matrix multiplication on multilevel memory architectures algorithms and experiments":
    also connected through other hyperedges:
      (none)
  Member "multi threaded sparse matrix matrix multiplication for many core and gpu architectures":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "sparse matrix multiplication with bandwidth restricted all to all communication")
  Member "porting of the dbcsr library for sparse matrix matrix multiplications to intel xeon phi systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "dbcsr a library for dense matrix multiplications on distributed gpu accelerated systems")
  Member "static graph challenge subgraph isomorphism":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "75 000 000 000 streaming inserts second using hierarchical hypersparse graphblas matrices")
  Member "a comparative study on exact triangle counting algorithms on the gpu":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fast gunrock subgraph matching gsm on gpus")
  Member "hypergraph partitioning for sparse matrix matrix multiplication":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "hypergraph cuts with general splitting functions")
  Member "locality aware parallel block sparse matrix matrix multiplication using the chunks and tasks programming model":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "parallelization and scalability analysis of inverse factorization using the chunks and tasks programming model")

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)