human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "λ nic interactive serverless compute on programmable smartnics"):
  Abstract: There is a growing interest in serverless compute, a cloud computing model that automates infrastructure resource-allocation and management while billing customers only for the resources they use. Workloads like stream processing benefit from high elasticity and fine-grain pricing of these serverless frameworks. However, so far, limited concurrency and high latency of server CPUs prohibit many interactive workloads (e.g., web servers and database clients) from taking advantage of serverless compute to achieve high performance. #R##N#In this paper, we argue that server CPUs are ill-suited to run serverless workloads (i.e., lambdas) and present $\lambda$-NIC, an open-source framework, that runs interactive workloads directly on a SmartNIC; more specifically an ASIC-based NIC that consists of a dense grid of Network Processing Unit (NPU) cores. $\lambda$-NIC leverages SmartNIC's proximity to the network and a vast array of NPU cores to simultaneously run thousands of lambdas on a single NIC with strict tail-latency guarantees. To ease development and deployment of lambdas, $\lambda$-NIC exposes an event-based programming abstraction, Match+Lambda, and a machine model that allows developers to compose and execute lambdas on SmartNICs easily. Our evaluation shows that $\lambda$-NIC achieves up to 880x and 736x improvements in workloads' response latency and throughput, respectively, while significantly reducing host CPU and memory usage.

Includes members:
  Member "scalable methods for 8 bit training of neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sparse weight activation training")
  Member "homa a receiver driven low latency transport protocol using network priorities":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a survey on recent advances in transport layer protocols")
  Member "comparative study of deep learning software frameworks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "high performance i o for large scale deep learning")
  Member "8 bit approximations for parallelism in deep learning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "learning home crowdsourced training of large neural networks using decentralized mixture of experts")

Question: Please tell me which class the source paper 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.NI(Networking and Internet Architecture)