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: "the impact of on chip communication on memory technologies for neuromorphic systems"
  Abstract: Emergent nanoscale non-volatile memory technologies with high integration density offer a promising solution to overcome the scalability limitations of CMOS-based neural networks architectures, by efficiently exhibiting the key principle of neural computation. Despite the potential improvements in computational costs, designing high-performance on-chip communication networks that support flexible, large-fanout connectivity remains as daunting task. In this paper, we elaborate on the communication requirements of large-scale neuromorphic designs, and point out the differences with the conventional network-on-chip architectures. We present existing approaches for on-chip neuromorphic routing networks, and discuss how new memory and integration technologies may help to alleviate the communication issues in constructing next-generation intelligent computing machines.

Connected through hyperedge HE-1 (induced by source paper "finally how many efficiencies the supercomputers have and what do they measure"):
  with members:
    - "the need for modern computing paradigm science applied to computing"
    - "the performance wall of parallelized sequential computing the dark performance and the roofline of performance gain"
    - "comparative benchmarking of cloud computing vendors with high performance linpack"
    - "how amdahl s low restricts supercomputer applications and building ever bigger supercomputers"
    - "limits on fundamental limits to computation"

Connected through hyperedge HE-2 (induced by source paper "the need for modern computing paradigm science applied to computing"):
  with members:
    - "challenges to keeping the computer industry centered in the us"
    - "how amdahl s low restricts supercomputer applications and building ever bigger supercomputers"
    - "a figure of merit for describing the performance of scaling of parallelization"
    - "limits on fundamental limits to computation"

Connected through hyperedge HE-3 (induced by source paper "fast and efficient information transmission with burst spikes in deep spiking neural networks"):
  with members:
    - "streaming mann a streaming based inference for energy efficient memory augmented neural networks"
    - "energy efficient inference accelerator for memory augmented neural networks on an fpga"
    - "quantized memory augmented neural networks"
    - "an efficient approach to boosting performance of deep spiking network training"
    - "eie efficient inference engine on compressed deep neural network"
    - "training deep spiking neural networks using backpropagation"
    - "deep compression compressing deep neural networks with pruning trained quantization and huffman coding"

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.AR(Hardware Architecture)