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 "chonda near data acceleration with concurrent host access"):
  Abstract: Near-data accelerators (NDAs) that are integrated with main memory have the potential for significant power and performance benefits. Fully realizing these benefits requires the large available memory capacity to be shared between the host and the NDAs in a way that permits both regular memory access by some applications and accelerating others with an NDA, avoids copying data, enables collaborative processing, and simultaneously offers high performance for both host and NDA. We identify and solve new challenges in this context: mitigating row-locality interference from host to NDAs, reducing read/write-turnaround overhead caused by fine-grain interleaving of host and NDA requests, architecting a memory layout that supports the locality required for NDAs and sophisticated address interleaving for host performance, and supporting both packetized and traditional memory interfaces. We demonstrate our approach in a simulated system that consists of a multi-core CPU and NDA-enabled DDR4 memory modules. We show that our mechanisms enable effective and efficient concurrent access using a set of microbenchmarks, and then demonstrate the potential of the system for the important stochastic variance-reduced gradient (SVRG) algorithm.

Includes members:
  Member "graphr accelerating graph processing using reram":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on graph processing accelerators challenges and opportunities")
  Member "drama exploiting dram addressing for cross cpu attacks":
    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")

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)