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: "euretile 2010 2012 summary first three years of activity of the european reference tiled experiment"
  Abstract: Abstract This is the summary of first three years of activity of the EURETILE FP7 project 247846. EURETILE investigates and implements brain-inspired and fault-tolerant foundational innovations to the system architecture of massively parallel tiled computer architectures and the corresponding programming paradigm. The execution targets are a many-tile HW platform, and a many-tile simulator. A set of SW process - HW tile mapping candidates is generated by the holistic SW tool-chain using a combination of analytic and bio-inspired methods. The Hardware dependent Software is then generated, providing OS services with maximum efficiency/minimal overhead. The many-tile simulator collects profiling data, closing the loop of the SW tool chain. Fine-grain parallelism inside processes is exploited by optimized intra-tile compilation techniques, but the project focus is above the level of the elementary tile. The elementary HW tile is a multi-processor, which includes a fault tolerant Distributed Network Processor (for inter-tile communication) and ASIP accelerators. Furthermore, EURETILE investigates and implements the innovations for equipping the elementary HW tile with high-bandwidth, low-latency brain-like inter-tile communication emulating 3 levels of connection hierarchy, namely neural columns, cortical areas and cortex, and develops a dedicated cortical simulation benchmark: DPSNN-STDP (Distributed Polychronous Spiking Neural Net with synaptic Spiking Time Dependent Plasticity). EURETILE leverages on the multi-tile HW paradigm and SW tool-chain developed by the FET-ACA SHAPES Integrated Project (2006-2009). The APE Parallel Computing Lab of INFN Roma is in charge of the EURETILE HW Design (QUonG system/APENet+ board/DNP (Distributed Network Processor) and Scientific Application Benchmarks. The Computer Engineering and Networks Laboratory (TIK) of ETH Zurich (Swiss Federal Institute of Technology) designs the high-level explicit parallel programming and automatic mapping tool (DOL/DAL) and a set of “Embedded Systems” benchmarks. The Software for Systems on Silicon (SSS) of the ISS institute of RWTH Aachen, investigates and provides the parallel simulation technology and scalable simulation-based profiling/debugging support. The TIMA Laboratory of the University Joseph Fourier in Grenoble explores and deploys the HdS (Hardware dependent Software) including the distributed OS architecture. TARGET Compiler Technologies, the Belgian leading provider of retargetable software tools and compilers for the design, programming, and verification of application-specific processors (ASIPs), is in charge of the HW/SW Co-design tools for custom components of the EURETILE architecture. Grant Agreement no. 247846 Call: FP7-ICT-2009-4 Objective FET-ICT-2009.8.1 Concurrent Tera-device Computing Scientific Coordinator: Pier Stanislao Paolucci, Istituto Nazionale di Fisica Nucleare, Roma, Italy Administrative Coordinator: Michela Giovagnoli, Istituto Nazionale di Fisica Nucleare, Roma, Italy

Connected through hyperedge HE-1 (induced by source paper "power energy and speed of embedded and server multi cores applied to distributed simulation of spiking neural networks arm in nvidia tegra vs intel xeon quad cores"):
  with members:
    - "distributed simulation of polychronous and plastic spiking neural networks strong and weak scaling of a representative mini application benchmark executed on a small scale commodity cluster"

Connected through hyperedge HE-2 (induced by source paper "euretile d7 3 dynamic dal benchmark coding measurements on mpi version of dpsnn stdp distributed plastic spiking neural net and improvements to other dal codes"):
  with members:
    - "distributed simulation of polychronous and plastic spiking neural networks strong and weak scaling of a representative mini application benchmark executed on a small scale commodity cluster"

Connected through hyperedge HE-3 (induced by source paper "a heterogeneous many core platform for experiments on scalable custom interconnects and management of fault and critical events applied to many process applications vol ii 2012 technical report"):
  with members:
    - "mutual watch dog networking distributed awareness of faults and critical events in petascale exascale systems"
    - "the distributed network processor a novel off chip and on chip interconnection network architecture"

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)