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 "an adaptive load balancer for graph analytical applications on gpus"):
  Abstract: Load balancing graph analytics workloads on GPUs is difficult because of the irregular nature of graph applications and the high variability in vertex degrees, particularly in power-law graphs. In this paper, we describe a novel load balancing scheme that aims to address this problem. Our scheme is implemented in the IrGL compiler to allow users to generate efficient load-balanced code for GPUs from high-level sequential programs. We evaluated several IrGL-generated load-balanced programs on up to 16 GPUs. Our experiments show that this scheme can achieve an average speed-up of 1.5x on inputs that suffer from severe load imbalance problems when previous state-of-the-art load-balancing schemes are used.

Includes members:
  Member "gunrock gpu graph analytics":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimizing ordered graph algorithms with graphit")
  Member "dynamic load balancing strategies for graph applications on gpus":
    also connected through other hyperedges:
      (none)
  Member "multi gpu graph analytics":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "dynamic merging of frontiers for accelerating the evaluation of betweenness centrality")
  Member "gunrock a high performance graph processing library on the gpu":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hygcn a gcn accelerator with hybrid architecture")
  Member "parallel breadth first search on distributed memory systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a systematic survey of general sparse matrix matrix multiplication")

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)