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 "improving the space time efficiency of processor oblivious matrix multiplication algorithms"):
  Abstract: Classic cache-oblivious parallel matrix multiplication algorithms achieve optimality either in time or space, but not both, which promotes lots of research on the best possible balance or tradeoff of such algorithms. We study modern processor-oblivious runtime systems and figure out several ways to improve algorithm's time bound while still bounding space and cache requirements to be asymptotically optimal. By our study, we give out sublinear time, optimal work, space and cache algorithms for both general matrix multiplication on a semiring and Strassen-like fast algorithm. Our experiments also show such algorithms have empirical advantages over classic counterparts. Our study provides new insights and research angles on how to optimize cache-oblivious parallel algorithms from both theoretical and empirical perspectives.

Includes members:
  Member "extending the nested parallel model to the nested dataflow model with provably efficient schedulers":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimal parallel algorithms in the binary forking model")
  Member "implementing strassen s algorithm with blis":
    also connected through other hyperedges:
      (none)
  Member "a framework for practical parallel fast matrix multiplication":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "deterministic combinatorial replacement paths and distance sensitivity oracles")
  Member "communication optimal parallel algorithm for strassen s matrix multiplication":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "engineering boolean matrix multiplication for multiple accelerator shared memory architectures")
  Member "minimizing communication in linear algebra":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "communication efficient jaccard similarity for high performance distributed genome comparisons")
  Member "memory efficient scheduling of strassen winograd s matrix multiplication algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "generic reductions for in place polynomial multiplication")

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)