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: "study of raspberry pi 2 quad core cortex a7 cpu cluster as a mini supercomputer"
  Abstract: High performance computing (HPC) devices is no longer exclusive for academic, R&D, or military purposes. The use of HPC device such as supercomputer now growing rapidly as some new area arise such as big data, and computer simulation. It makes the use of supercomputer more inclusive. Today's supercomputer has a huge computing power, but requires an enormous amount of energy to operate. In contrast a single board computer (SBC), i.e., Raspberry Pi has minimum computing power, but requires a small amount of energy to operate, and as a bonus it is small and cheap. This paper covers the result of utilizing many Raspberry Pi 2 SBCs, a quad-core Cortex-A7 900 MHz, as a cluster to compensate its computing power. The high performance linpack (HPL) is used to benchmark the computing power, and a power meter with resolution 10mV / 10mA is used to measure the power consumption. The experiment shows that the increase of number of cores in every SBC member in a cluster is not giving significant increase in computing power. This experiment gives a recommendation that 4 nodes is a maximum number of nodes for SBC cluster based on the characteristic of computing performance and power consumption.

Connected through hyperedge HE-1 (induced by source paper "hpc as a service a naive model"):
  with members:
    - "performance comparison of mpich and mpi4py on raspberry pi 3b beowulf cluster"

Connected through hyperedge HE-2 (induced by source paper "performance comparison of mpich and mpi4py on raspberry pi 3b beowulf cluster"):
  with members:
    - "affordable and energy efficient cloud computing clusters the bolzano raspberry pi cloud cluster experiment"

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)