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: "high level python abstractions for optimal checkpointing in inversion problems"
  Abstract: Inversion and PDE-constrained optimization problems often rely on solving the adjoint problem to calculate the gradient of the objec- tive function. This requires storing large amounts of intermediate data, setting a limit to the largest problem that might be solved with a given amount of memory available. Checkpointing is an approach that can reduce the amount of memory required by redoing parts of the computation instead of storing intermediate results. The Revolve checkpointing algorithm o ers an optimal schedule that trades computational cost for smaller memory footprints. Integrat- ing Revolve into a modern python HPC code and combining it with code generation is not straightforward. We present an API that makes checkpointing accessible from a DSL-based code generation environment along with some initial performance gures with a focus on seismic applications.

Connected through hyperedge HE-1 (induced by source paper "devito v3 1 0 an embedded domain specific language for finite differences and geophysical exploration"):
  with members:
    - "simflowny 2 an upgraded platform for scientific modelling and simulation"
    - "architecture and performance of devito a system for automated stencil computation"
    - "optimised finite difference computation from symbolic equations"
    - "performance prediction of finite difference solvers for different computer architectures"
    - "firedrake automating the finite element method by composing abstractions"
    - "opensbli a framework for the automated derivation and parallel execution of finite difference solvers on a range of computer architectures"
    - "cross loop optimization of arithmetic intensity for finite element local assembly"
    - "automated derivation of the adjoint of high level transient finite element programs"

Connected through hyperedge HE-2 (induced by source paper "an event driven approach to serverless seismic imaging in the cloud"):
  with members:
    - "devito v3 1 0 an embedded domain specific language for finite differences and geophysical exploration"
    - "comparative benchmarking of cloud computing vendors with high performance linpack"
    - "architecture and performance of devito a system for automated stencil computation"
    - "a unified 2d 3d large scale software environment for nonlinear inverse problems"
    - "jinv a flexible julia package for pde parameter estimation"
    - "deep residual learning for image recognition"
    - "adam a method for stochastic optimization"
    - "the numpy array a structure for efficient numerical computation"

Connected through hyperedge HE-3 (induced by source paper "training on the edge the why and the how"):
  with members:
    - "supporting very large models using automatic dataflow graph partitioning"
    - "gpipe efficient training of giant neural networks using pipeline parallelism"
    - "cutting down training memory by re fowarding"
    - "optimal gradient checkpoint search for arbitrary computation graphs"
    - "training deep nets with sublinear memory cost"
    - "on large batch training for deep learning generalization gap and sharp minima"
    - "mxnet a flexible and efficient machine learning library for heterogeneous distributed systems"

Connected through hyperedge HE-4 (induced by source paper "devito an embedded domain specific language for finite differences and geophysical exploration"):
  with members:
    - "simflowny 2 an upgraded platform for scientific modelling and simulation"
    - "architecture and performance of devito a system for automated stencil computation"
    - "performance prediction of finite difference solvers for different computer architectures"
    - "opensbli a framework for the automated derivation and parallel execution of finite difference solvers on a range of computer architectures"
    - "cross loop optimization of arithmetic intensity for finite element local assembly"
    - "automated derivation of the adjoint of high level transient finite element programs"

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.MS(Mathematical Software)