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 "enabling practical processing in and near memory for data intensive computing"):
  Abstract: Modern computing systems suffer from the dichotomy between computation on one side, which is performed only in the processor (and accelerators), and data storage/movement on the other, which all other parts of the system are dedicated to. Due to this dichotomy, data moves a lot in order for the system to perform computation on it. Unfortunately, data movement is extremely expensive in terms of energy and latency, much more so than computation. As a result, a large fraction of system energy is spent and performance is lost solely on moving data in a modern computing system. #R##N#In this work, we re-examine the idea of reducing data movement by performing Processing in Memory (PIM). PIM places computation mechanisms in or near where the data is stored (i.e., inside the memory chips, in the logic layer of 3D-stacked logic and DRAM, or in the memory controllers), so that data movement between the computation units and memory is reduced or eliminated. While the idea of PIM is not new, we examine two new approaches to enabling PIM: 1) exploiting analog properties of DRAM to perform massively-parallel operations in memory, and 2) exploiting 3D-stacked memory technology design to provide high bandwidth to in-memory logic. We conclude by discussing work on solving key challenges to the practical adoption of PIM.

Includes members:
  Member "processing data where it makes sense enabling in memory computation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "rowhammer a retrospective")
  Member "rowhammer a retrospective":
    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 "shouji a fast and efficient pre alignment filter for sequence alignment":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a workload and programming ease driven perspective of processing in memory")
  Member "enabling the adoption of processing in memory challenges mechanisms future research directions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (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-5 (induced by source paper "are we susceptible to rowhammer an end to end methodology for cloud providers")
  Member "using ecc dram to adaptively increase memory capacity":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "processing data where it makes sense enabling in memory computation")
  Member "understanding and improving the latency of dram based memory systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "eden enabling energy efficient high performance deep neural network inference using approximate dram")
  Member "buddy ram improving the performance and efficiency of bulk bitwise operations using dram":
    also connected through other hyperedges:
      - Hyperedge HE-8 (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.DC(Distributed, Parallel, and Cluster Computing)