human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "efficient multicore aware parallelization strategies for iterative stencil computations"
  Abstract: Abstract   Stencil computations consume a major part of runtime in many scientific simulation codes. As prototypes for this class of algorithms we consider the iterative Jacobi and Gauss-Seidel smoothers and aim at highly efficient parallel implementations for cache-based multicore architectures. Temporal cache blocking is a known advanced optimization technique, which can reduce the pressure on the memory bus significantly. We apply and refine this optimization for a recently presented temporal blocking strategy designed to explicitly utilize multicore characteristics. Especially for the case of Gauss-Seidel smoothers we show that simultaneous multi-threading (SMT) can yield substantial performance improvements for our optimized algorithm on some architectures.

Connected through hyperedge HE-1 (induced by source paper "multi dimensional intra tile parallelization for memory starved stencil computations"):
  with members:
    - "quantifying performance bottlenecks of stencil computations using the execution cache memory model"
    - "multicore optimized wavefront diamond blocking for optimizing stencil updates"
    - "optimizing the performance of streaming numerical kernels on the ibm blue gene p powerpc 450 processor"
    - "leveraging shared caches for parallel temporal blocking of stencil codes on multicore processors and clusters"
    - "introducing a performance model for bandwidth limited loop kernels"

Connected through hyperedge HE-2 (induced by source paper "tight bounds for low dimensional star stencils in the parallel external memory model"):
  with members:
    - "communication optimal parallel algorithm for strassen s matrix multiplication"
    - "minimizing communication in linear algebra"

Connected through hyperedge HE-3 (induced by source paper "likwid a lightweight performance oriented tool suite for x86 multicore environments"):
  with members:
    - "multicore aware parallel temporal blocking of stencil codes for shared and distributed memory"

Connected through hyperedge HE-4 (induced by source paper "likwid a lightweight performance oriented tool suite for x86 multicore environments"):
  with members:
    - "multicore aware parallel temporal blocking of stencil codes for shared and distributed memory"

Question: Please tell me which class the center node 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.PF(Performance)