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 "a 588 gb s ldpc decoder based on finite alphabet message passing"):
  Abstract: An ultrahigh throughput low-density parity-check (LDPC) decoder with an unrolled full-parallel architecture is proposed, which achieves the highest decoding throughput compared to previously reported LDPC decoders in the literature. The decoder benefits from a serial message-transfer approach between the decoding stages to alleviate the well-known routing congestion problem in parallel LDPC decoders. Furthermore, a finite-alphabet message passing algorithm is employed to replace the VN update rule of the standard min-sum (MS) decoder with lookup tables, which are designed in a way that maximizes the mutual information between decoding messages. The proposed algorithm results in an architecture with reduced bit-width messages, leading to a significantly higher decoding throughput and to a lower area compared to an MS decoder when serial message transfer is used. The architecture is placed and routed for the standard MS reference decoder and for the proposed finite-alphabet decoder using a custom pseudo-hierarchical backend design strategy to further alleviate routing congestions and to handle the large design. Postlayout results show that the finite-alphabet decoder with the serial message-transfer architecture achieves a throughput as large as 588 Gb/s with an area of 16.2 mm#N# 2#N# and dissipates an average power of 22.7 pJ per decoded bit in a 28-nm fully depleted silicon on isulator library. Compared to the reference MS decoder, this corresponds to 3.1 times smaller area and 2 times better energy efficiency.

Includes members:
  Member "quantized message passing for ldpc codes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mutual information maximizing quantized belief propagation decoding of ldpc codes")
  Member "a fully unrolled ldpc decoder based on quantized message passing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a multi gbps unrolled hardware list decoder for a systematic polar code")

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.AR(Hardware Architecture)