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 "d range using commodity dram devices to generate true random numbers with low latency and high throughput"):
  Abstract: We propose a new DRAM-based true random number generator (TRNG) that leverages DRAM cells as an entropy source. The key idea is to intentionally violate the DRAM access timing parameters and use the resulting errors as the source of randomness. Our technique specifically decreases the DRAM row activation latency (timing parameter tRCD) below manufacturer-recommended specifications, to induce read errors, or activation failures, that exhibit true random behavior. We then aggregate the resulting data from multiple cells to obtain a TRNG capable of providing a high throughput of random numbers at low latency. #R##N#To demonstrate that our TRNG design is viable using commodity DRAM chips, we rigorously characterize the behavior of activation failures in 282 state-of-the-art LPDDR4 devices from three major DRAM manufacturers. We verify our observations using four additional DDR3 DRAM devices from the same manufacturers. Our results show that many cells in each device produce random data that remains robust over both time and temperature variation. We use our observations to develop D-RanGe, a methodology for extracting true random numbers from commodity DRAM devices with high throughput and low latency by deliberately violating the read access timing parameters. We evaluate the quality of our TRNG using the commonly-used NIST statistical test suite for randomness and find that D-RaNGe: 1) successfully passes each test, and 2) generates true random numbers with over two orders of magnitude higher throughput than the previous highest-throughput DRAM-based TRNG.

Includes members:
  Member "enabling the adoption of processing in memory challenges mechanisms future research directions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "machine learning systems for highly distributed and rapidly growing data")
  Member "the rowhammer problem and other issues we may face as memory becomes denser":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "are we susceptible to rowhammer an end to end methodology for cloud providers")
  Member "nano intrinsic true random number generation":
    also connected through other hyperedges:
      (none)
  Member "reducing dram latency at low cost by exploiting heterogeneity":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "processing data where it makes sense enabling in memory computation")
  Member "simple dram and virtual memory abstractions to enable highly efficient memory systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "processing data where it makes sense enabling in memory computation")
  Member "improving dram performance by parallelizing refreshes with accesses":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "are we susceptible to rowhammer an end to end methodology for cloud providers")
  Member "ensuring high quality randomness in cryptographic key generation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "dataplant in dram security mechanisms for low cost devices")

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)