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 "distributed memory forest of octrees raycasting"):
  Abstract: We present an MPI-parallel algorithm for the in-situ visualization of computational data that is built around a distributed linear forest-of-octrees data structure. Such octrees are frequently used in element-based numerical simulations; they store the leaves of the tree that are local in the curent parallel partition. #R##N#We proceed in three stages. First, we prune all elements whose bounding box is not visible by a parallel top-down traversal, and repartition the remaining ones for load-balancing. Second, we intersect each element with every ray passing its box to derive color and opacity values for the ray segment. To reduce data, we aggregate the segments up the octree in a strictly distributed fashion in cycles of coarsening and repartition. Third, we composite all remaining ray segments to a tiled partition of the image and write it to disk using parallel I/O. #R##N#The scalability of the method derives from three concepts: By exploiting the space filling curve encoding of the octrees and by relying on recently developed tree algorithms for top-down partition traversal, we are able to determine sender/receiver pairs without handshaking and/or collective communication. Furthermore, by partnering the linear traversal of tree leaves with the group action of the attenuation/emission ODE along each segment, we avoid back-to-front sorting of elements throughout. Lastly, the method is problem adaptive with respect to the refinement and partition of the elements and to the accuracy of ODE integration.

Includes members:
  Member "parallel tree algorithms for amr and non standard data access":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the deal ii finite element library design features and insights")
  Member "coarse mesh partitioning for tree based amr":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an optimized parallel computation of the ghost layer for adaptive hybrid forest meshes")
  Member "recursive algorithms for distributed forests of octrees":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an optimized parallel computation of the ghost layer for adaptive hybrid forest meshes")

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)