human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "swift using task based parallelism fully asynchronous communication and graph partition based domain decomposition for strong scaling on more than 100 000 cores"
  Abstract: We present a new open-source cosmological code, called SWIFT, designed to solve the equations of hydrodynamics using a particle-based approach (Smooth Particle Hydrodynamics) on hybrid shared / distributed-memory architectures. SWIFT was designed from the bottom up to provide excellent strong scaling on both commodity clusters (Tier-2 systems) and Top100-supercomputers (Tier-0 systems), without relying on architecture-specific features or specialized accelerator hardware. This performance is due to three main computational approaches:   • Task-based parallelism for shared-memory parallelism, which provides fine-grained load balancing and thus strong scaling on large numbers of cores.   • Graph-based domain decomposition, which uses the task graph to decompose the simulation domain such that the work, as opposed to just the data, as is the case with most partitioning schemes, is equally distributed across all nodes.   • Fully dynamic and asynchronous communication, in which communication is modelled as just another task in the task-based scheme, sending data whenever it is ready and deferring on tasks that rely on data from other nodes until it arrives.   In order to use these approaches, the code had to be re-written from scratch, and the algorithms therein adapted to the task-based paradigm. As a result, we can show upwards of 60% parallel efficiency for moderate-sized problems when increasing the number of cores 512-fold, on both x86-based and Power8-based architectures.

Connected through hyperedge HE-1 (induced by source paper "honing and proofing astrophysical codes on the road to exascale experiences from code modernization on many core systems"):
  with members:
    - "energy efficiency features of the intel skylake sp processor and their impact on performance"
    - "performance optimisation of smoothed particle hydrodynamics algorithms for multi many core architectures"
    - "optimization and parallelization of b spline based orbital evaluations in qmc on multi many core shared memory processors"

Connected through hyperedge HE-2 (induced by source paper "a high level characterisation and generalisation of communication avoiding programming techniques"):
  with members:
    - "parallel performance of algebraic multigrid domain decomposition amg dd"
    - "stop talking to me a communication avoiding ader dg realisation"
    - "enclave tasking for discontinuous galerkin methods on dynamically adaptive meshes"
    - "two particle in grid realisations on spacetrees"
    - "algebraic geometric matrix free multigrid on dynamically adaptive cartesian meshes"
    - "asynchronous mpi for the masses"

Connected through hyperedge HE-3 (induced by source paper "tasks unlimited lightweight task offloading exploiting mpi wait times for parallel adaptive mesh refinement"):
  with members:
    - "the peano software parallel automaton based dynamically adaptive grid traversals"
    - "exahype an engine for parallel dynamically adaptive simulations of wave problems"
    - "stop talking to me a communication avoiding ader dg realisation"
    - "studies on the energy and deep memory behaviour of a cache oblivious task based hyperbolic pde solver"
    - "enclave tasking for discontinuous galerkin methods on dynamically adaptive meshes"

Connected through hyperedge HE-4 (induced by source paper "swift maintaining weak scalability with a dynamic range of 10 4 in time step size to harness extreme adaptivity"):
  with members:
    - "efficient and scalable algorithms for smoothed particle hydrodynamics on hybrid shared distributed memory architectures"

Question: Please tell me which class the center node 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)