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: "architectural space exploration of heterogeneous reliability and checkpointing modes for out of order superscalar processors"
  Abstract: State-of-the-art reliability techniques and mechanisms deploy full-scale redundancy, like double or triple modular redundancy (DMR, TMR), on different layers of the computing stack to detect and/or correct such transient faults. However, the techniques relying on full-scale redundancy incur significant area, performance, and/or power overheads, which might not always be feasible/practical due to system constraints such as deadlines and available power budget for the full chip (or a processor core). In this work, we propose a novel design methodology to generate and explore the architectural-space of heterogeneous reliability modes for out-of-order superscalar multi-core processors. These heterogeneous modes enable varying reliability and power/area trade-offs, from which an optimal configuration can be chosen at run time to meet the reliability requirements of a given system while reducing the corresponding power overheads (or solving the inverse problem, i.e., maximizing the reliability under a given power constraint). Our experimental results show that a pareto-optimal heterogeneous reliability mode reduces the core vulnerability by 87%, on average, across multiple application workloads, with area and power overheads of 10% and 43%, respectively. To further enhance the design space of heterogeneous reliability modes, we investigate the effectiveness of combining different processor state compression techniques like Distributed Multi-threaded Checkpointing (DMTCP), Hash-based Incremental Checkpointing (HBICT) and GNU zip, such that the correct processor state can be recovered once a fault is detected. We reduced the checkpoint sizes by a factor of ~6× using a unique combination of different state compression techniques.

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)