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 characterization of hidden processor memory hierarchies"
  Abstract: A processor’s memory hierarchy has a major impact on the performance of running code. However, computing platforms, where the actual hardware characteristics are hidden from both the end user and the tools that mediate execution, such as a compiler, a JIT and a runtime system, are used more and more, for example, performing large scale computation in cloud and cluster. Even worse, in such environments, a single computation may use a collection of processors with dissimilar characteristics. Ignorance of the performance-critical parameters of the underlying system makes it difficult to improve performance by optimizing the code or adjusting runtime-system behaviors; it also makes application performance harder to understand.

Connected through hyperedge HE-1 (induced by source paper "nanobench a low overhead tool for running microbenchmarks on x86 systems"):
  with members:
    - "uops info characterizing latency throughput and port usage of instructions on intel microarchitectures"
    - "cachequery learning replacement policies from hardware caches"
    - "reload refresh abusing cache replacement policies to perform stealthy cache attacks"
    - "spectre attacks exploiting speculative execution"
    - "theory and practice of finding eviction sets"
    - "dissecting gpu memory hierarchy through microbenchmarking"
    - "likwid a lightweight performance oriented tool suite for x86 multicore environments"
    - "likwid a lightweight performance oriented tool suite for x86 multicore environments"

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.DC(Distributed, Parallel, and Cluster Computing)