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 "benchmarking data analysis and machine learning applications on the intel knl many core processor"):
  Abstract: Knights Landing (KNL) is the code name for the second-generation Intel Xeon Phi product family. KNL has generated significant interest in the data analysis and machine learning communities because its new many-core architecture targets both of these workloads. The KNL many-core vector processor design enables it to exploit much higher levels of parallelism. At the Lincoln Laboratory Supercomputing Center (LLSC), the majority of users are running data analysis applications such as MATLAB and Octave. More recently, machine learning applications, such as the UC Berkeley Caffe deep learning framework, have become increasingly important to LLSC users. Thus, the performance of these applications on KNL systems is of high interest to LLSC users and the broader data analysis and machine learning communities. Our data analysis benchmarks of these application on the Intel KNL processor indicate that single-core double-precision generalized matrix multiply (DGEMM) performance on KNL systems has improved by ∼3.5× compared to prior Intel Xeon technologies. Our data analysis applications also achieved ∼60% of the theoretical peak performance. Also a performance comparison of a machine learning application, Caffe, between the two different Intel CPUs, Xeon E5 v3 and Xeon Phi 7210, demonstrated a 2.7× improvement on a KNL node.

Includes members:
  Member "llmapreduce multi level map reduce for high performance data analysis":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hyperscaling internet graph analysis with d4m on the mit supercloud")
  Member "co design of a particle in cell plasma simulation code for intel xeon phi a first look at knights landing":
    also connected through other hyperedges:
      (none)
  Member "enabling on demand database computing with mit supercloud database management system":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "ai enabling technologies a survey")
  Member "big data strategies for data center infrastructure management using a 3d gaming platform":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "securing hpc using federated authentication")
  Member "d4m bringing associative arrays to database engines":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "ai enabling technologies a survey")
  Member "achieving 100 000 000 database inserts per second using accumulo and d4m":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "75 000 000 000 streaming inserts second using hierarchical hypersparse graphblas matrices")
  Member "going deeper with convolutions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "discrimination aware network pruning for deep model compression")
  Member "computing on masked data a high performance method for improving big data veracity":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "securing hpc using federated authentication")

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.PF(Performance)