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 "in dram bulk bitwise execution engine"):
  Abstract: Many applications heavily use bitwise operations on large bitvectors as part of their computation. In existing systems, performing such bulk bitwise operations requires the processor to transfer a large amount of data on the memory channel, thereby consuming high latency, memory bandwidth, and energy. In this paper, we describe Ambit, a recently-proposed mechanism to perform bulk bitwise operations completely inside main memory. Ambit exploits the internal organization and analog operation of DRAM-based memory to achieve low cost, high performance, and low energy. Ambit exposes a new bulk bitwise execution model to the host processor. Evaluations show that Ambit significantly improves the performance of several applications that use bulk bitwise operations, including databases.

Includes members:
  Member "shouji a fast and efficient pre alignment filter for sequence alignment":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a workload and programming ease driven perspective of processing in memory")
  Member "d range using commodity dram devices to generate true random numbers with low latency and high throughput":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "eden enabling energy efficient high performance deep neural network inference using approximate dram")
  Member "what your dram power models are not telling you lessons from a detailed experimental study":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "processing data where it makes sense enabling in memory computation")
  Member "neural cache bit serial in cache acceleration of deep neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "accelerating generalized linear models with mlweaving a one size fits all system for any precision learning technical report")
  Member "understanding reduced voltage operation in modern dram chips characterization analysis and mechanisms":
    also connected through other hyperedges:
      (none)
  Member "reducing dram latency at low cost by exploiting heterogeneity":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "processing data where it makes sense enabling in memory computation")
  Member "xnor net imagenet classification using binary convolutional neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "discrimination aware network pruning for deep model compression")
  Member "simple dram and virtual memory abstractions to enable highly efficient memory systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "processing data where it makes sense enabling in memory computation")

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)