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: "a figure of merit for describing the performance of scaling of parallelization"
  Abstract: With the spread of multi- and many-core processors more and more typical task is to re-implement some source code written originally for a single processor to run on more than one cores. Since it is a serious investment, it is important to decide how much efforts pays off, and whether the resulting implementation has as good performability as it could be. The Amdahl's law provides some theoretical upper limits for the performance gain reachable through parallelizing the code, but it needs the detailed architectural knowledge of the program code, does not consider the housekeeping activity needed for parallelization and cannot tell how the actual stage of parallelization implementation performs. The present paper suggests a quantitative measure for that goal. This figure of merit is derived experimentally, from measured running time, and number of threads/cores. It can be used to quantify the used parallelization technology, the connection between the computing units, the acceleration technology under the given conditions, communication method within SoC, or the performance of the software team/compiler.

Connected through hyperedge HE-1 (induced by source paper "the need for modern computing paradigm science applied to computing"):
  with members:
    - "the impact of on chip communication on memory technologies for neuromorphic systems"
    - "challenges to keeping the computer industry centered in the us"
    - "how amdahl s low restricts supercomputer applications and building ever bigger supercomputers"
    - "limits on fundamental limits to computation"

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)