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 "eva cim a system level performance and energy evaluation framework for computing in memory architectures"):
  Abstract: Computing-in-Memory (CiM) architectures aim to reduce costly data transfers by performing arithmetic and logic operations in memory and hence relieve the pressure due to the memory wall. However, determining whether a given workload can really benefit from CiM, which memory hierarchy and what device technology should be adopted by a CiM architecture requires in-depth study that is not only time consuming but also demands significant expertise in architectures and compilers. This paper presents an energy evaluation framework, Eva-CiM, for systems based on CiM architectures. Eva-CiM encompasses a multi-level (from device to architecture) comprehensive tool chain by leveraging existing modeling and simulation tools such as GEM5, McPAT [2] and DESTINY [3]. To support high-confidence prediction, rapid design space exploration and ease of use, Eva-CiM introduces several novel modeling/analysis approaches including models for capturing memory access and dependency-aware ISA traces, and for quantifying interactions between the host CPU and CiM modules. Eva-CiM can readily produce energy estimates of the entire system for a given program, a processor architecture, and the CiM array and technology specifications. Eva-CiM is validated by comparing with DESTINY [3] and [4], and enables findings including practical contributions from CiM-supported accesses, CiM-sensitive benchmarking as well as the pros and cons of increased memory size for CiM. Eva-CiM also enables exploration over different configurations and device technologies, showing 1.3-6.0X energy improvement for SRAM and 2.0-7.9X for FeFET-RAM, respectively.

Includes members:
  Member "x sram enabling in memory boolean computations in cmos static random access memories":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "an overview of in memory processing with emerging non volatile memory for data intensive applications")
  Member "computing in memory with spin transfer torque magnetic ram":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a new mram based process in memory accelerator for efficient neural network training with floating point precision")
  Member "buddy ram improving the performance and efficiency of bulk bitwise operations using dram":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "mixed precision deep learning based on computational memory")

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)