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 "collecting and presenting reproducible intranode stencil performance inspect"):
  Abstract: Stencil algorithms have been receiving considerable interest in HPC research for decades. The techniques used to approach multi-core stencil performance modeling and engineering span basic runtime measurements, elaborate performance models, detailed hardware counter analysis, and thorough scaling behavior evaluation. Due to the plurality of approaches and stencil patterns, we set out to develop a generalizable methodology for reproducible measurements accompanied by state-of-the-art performance models. Our open-source toolchain, and collected results are publicly available in the "Intranode Stencil Performance Evaluation Collection" (INSPECT). We present the underlying methodologies, models and tools involved in gathering and documenting the performance behavior of a collection of typical stencil patterns across multiple architectures and hardware configuration options. Our aim is to endow performance-aware application developers with reproducible baseline performance data and validated models to initiate a well-defined process of performance assessment and optimization.

Includes members:
  Member "uops info characterizing latency throughput and port usage of instructions on intel microarchitectures":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "nanobench a low overhead tool for running microbenchmarks on x86 systems")
  Member "on the accuracy and usefulness of analytic energy models for contemporary multicore processors":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "analytic performance modeling and analysis of detailed neuron simulations")
  Member "automated instruction stream throughput prediction for intel and amd microarchitectures":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "smotherspectre exploiting speculative execution through port contention")
  Member "an analysis of core and chip level architectural features in four generations of intel server processors":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "understanding hpc benchmark performance on intel broadwell and cascade lake processors")
  Member "kerncraft a tool for analytic performance modeling of loop kernels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "analytic performance modeling and analysis of detailed neuron simulations")
  Member "quantifying performance bottlenecks of stencil computations using the execution cache memory model":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "desynchronization and wave pattern formation in mpi parallel and hybrid memory bound programs")
  Member "multicore optimized wavefront diamond blocking for optimizing stencil updates":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a versatile software systolic execution model for gpu memory bound kernels")
  Member "likwid a lightweight performance oriented tool suite for x86 multicore environments":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "lbmpy a flexible code generation toolkit for highly efficient lattice boltzmann simulations")

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.PF(Performance)