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 "kerncraft a tool for analytic performance modeling of loop kernels"):
  Abstract: Achieving optimal program performance requires deep insight into the interaction between hardware and software. For software developers without an in-depth background in computer architecture, understanding and fully utilizing modern architectures is close to impossible. Analytic loop performance modeling is a useful way to understand the relevant bottlenecks of code execution based on simple machine models. The Roofline Model and the Execution-Cache-Memory (ECM) model are proven approaches to performance modeling of loop nests. In comparison to the Roofline model, the ECM model can also describes the single-core performance and saturation behavior on a multicore chip.We give an introduction to the Roofline and ECM models, and to stencil performance modeling using layer conditions (LC). We then present Kerncraft, a tool that can automatically construct Roofline and ECM models for loop nests by performing the required code, data transfer, and LC analysis. The layer condition analysis allows to predict optimal spatial blocking factors for loop nests. Together with the models it enables an ab-initio estimate of the potential benefits of loop blocking optimizations and of useful block sizes. In cases where LC analysis is not easily possible, Kerncraft supports a cache simulator as a fallback option. Using a 25-point long-range stencil we demonstrate the usefulness and predictive power of the Kerncraft tool.

Includes members:
  Member "ghost building blocks for high performance sparse linear algebra on heterogeneous systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "performance engineering for real and complex tall skinny matrix multiplication kernels on gpus")
  Member "quantifying performance bottlenecks of stencil computations using the execution cache memory model":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "desynchronization and wave pattern formation in mpi parallel and hybrid memory bound programs")
  Member "automatic loop kernel analysis and performance modeling with kerncraft":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "uops info characterizing latency throughput and port usage of instructions on intel microarchitectures")
  Member "chip level and multi node analysis of energy optimized lattice boltzmann cfd simulations":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "bridging the architecture gap abstracting performance relevant properties of modern server processors")
  Member "likwid a lightweight performance oriented tool suite for x86 multicore environments":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "lbmpy a flexible code generation toolkit for highly efficient lattice boltzmann simulations")
  Member "likwid a lightweight performance oriented tool suite for x86 multicore environments":
    also connected through other hyperedges:
      - Hyperedge HE-6 (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)