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 "yet another tensor toolbox for discontinuous galerkin methods and other applications"):
  Abstract: The numerical solution of partial differential equations is at the heart of many grand challenges in supercomputing. Solvers based on high-order discontinuous Galerkin (DG) discretisation have been shown to scale on large supercomputers with excellent performance and efficiency, if the implementation exploits all levels of parallelism and is tailored to the specific architecture. However, every year new supercomputers emerge and the list of hardware-specific considerations grows, simultaneously with the list of desired features in a DG code. Thus we believe that a sustainable DG code needs an abstraction layer to implement the numerical scheme in a suitable language. We explore the possibility to abstract the numerical scheme as small tensor operations, describe them in a domain-specific language (DSL) resembling the Einstein notation, and to map them to existing code generators which generate small matrix matrix multiplication routines. The compiler for our DSL implements classic optimisations that are used for large tensor contractions, and we present novel optimisation techniques such as equivalent sparsity patterns and optimal index permutations for temporary tensors. Our application examples, which include the earthquake simulation software SeisSol, show that the generated kernels achieve over 50 % peak performance while the DSL considerably simplifies the implementation.

Includes members:
  Member "design of a high performance gemm like tensor tensor multiplication":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "implementing strassen s algorithm with cutlass on nvidia volta gpus")
  Member "high performance tensor contraction without transposition":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a parallel sparse tensor benchmark suite on cpus and gpus")
  Member "madness a multiresolution adaptive numerical environment for scientific simulation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hptt a high performance tensor transposition c library")
  Member "tensor contractions with extended blas kernels on cpu and gpu":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "high performance deep learning via a single building block")
  Member "cross loop optimization of arithmetic intensity for finite element local assembly":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "devito v3 1 0 an embedded domain specific language for finite differences and geophysical exploration")
  Member "towards an efficient use of the blas library for multilinear tensor contractions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "spin summations a high performance perspective")
  Member "performance modeling for dense linear algebra":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "linnea automatic generation of efficient linear algebra programs")

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.MS(Mathematical Software)