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: "performance portable many core plasma simulations porting picongpu to openpower and beyond"
  Abstract: With the appearance of the heterogeneous platform OpenPower, many-core accelerator devices have been coupled with Power host processors for the first time. Towards utilizing their full potential, it is worth investigating performance portable algorithms that allow to choose the best-fitting hardware for each domain-specific compute task. Suiting even the high level of parallelism on modern GPGPUs, our presented approach relies heavily on abstract meta-programming techniques, which are essential to focus on fine-grained tuning rather than code porting. With this in mind, the CUDA-based open-source plasma simulation code PIConGPU is currently being abstracted to support the heterogeneous OpenPower platform using our fast porting interface cupla, which wraps the abstract parallel C++11 kernel acceleration library Alpaka.

Connected through hyperedge HE-1 (induced by source paper "evaluation of performance portability frameworks for the implementation of a particle in cell code"):
  with members:
    - "tuning and optimization for a variety of many core architectures without changing a single line of implementation code using the alpaka library"
    - "alpaka an abstraction library for parallel kernel acceleration"
    - "likwid a lightweight performance oriented tool suite for x86 multicore environments"
    - "likwid a lightweight performance oriented tool suite for x86 multicore environments"

Connected through hyperedge HE-2 (induced by source paper "on the scalability of data reduction techniques in current and upcoming hpc systems from an application perspective"):
  with members:
    - "significantly improving lossy compression for scientific data sets based on multidimensional prediction and error controlled quantization"
    - "alpaka an abstraction library for parallel kernel acceleration"
    - "in situ steerable hardware independent and data structure agnostic visualization with isaac"

Connected through hyperedge HE-3 (induced by source paper "tuning and optimization for a variety of many core architectures without changing a single line of implementation code using the alpaka library"):
  with members:
    - "alpaka an abstraction library for parallel kernel acceleration"

Connected through hyperedge HE-4 (induced by source paper "in situ steerable hardware independent and data structure agnostic visualization with isaac"):
  with members:
    - "alpaka an abstraction library for parallel kernel acceleration"

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)