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 "advances in run time performance and interoperability for the adapteva epiphany coprocessor"):
  Abstract: The energy-efficient Adapteva Epiphany architecture exhibits massive many-core scalability in a physically compact 2D array of RISC cores with a fast network-on-chip (NoC). The architecture presents many features and constraints which contribute to software design challenges for the application developer. Addressing these challenges within the software stack that supports application development is critical to improving productivity and expanding the range of applications for the architecture. We report here on advances that have been made in the COPRTHR-2 software stack targeting the Epiphany architecture that address critical issues identified in previous work. Specifically, we describe improvements that bring greater control and precision to the design of compact compiled binary programs in the context of the limited per-core local memory of the architecture. We describe a new design for run-time support that has been implemented to dramatically improve the program load and execute performance and capabilities. Finally, we describe developments that advance host-coprocessor interoperability to expand the functionality available to the application developer.

Includes members:
  Member "parallel programming model for the epiphany many core coprocessor using threaded mpi":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "an openshmem implementation for the adapteva epiphany coprocessor")
  Member "kickstarting high performance energy efficient manycore architectures with epiphany":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a survey on distributed machine learning")

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)