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 "parallel database recovery for multicore main memory databases"):
  Abstract: Main-memory database systems for multicore servers can achieve excellent performance when processing massive volume of OLTP workloads. But crash-resilience mechanism, or namely loggingand-replay, can either degrade the performance of transaction processing or slow down the process of failure recovery. In this paper, we show that, by exploiting application semantics, it is possible to achieve speedy failure recovery without introducing any costly logging overhead to the execution of online transactions. We propose TARS, a parallel log-recovery mechanism that is specifically designed for lightweight, coarse-grained command-logging approach. TARS leverages a combination of static and dynamic analyses to parallelize the log replay: at compile time, TARS decomposes stored procedures by carefully analyzing dependencies within and across programs; at recovery time, a re-execution schedule with a high degree of parallelism is attained through lightweight one-pass scans over transaction parameter values. As such, recovery latency is remarkably minimized. We evaluated TARS in a main-memory database prototype running on a 40-core server. Compared to the state-of-the-art mechanisms, TARS yields significantly higher recovery rate without compromising the efficiency of transaction processing.

Includes members:
  Member "automatic partitioning of database applications":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "scheduling oltp transactions via machine learning")
  Member "implementing performance competitive logical recovery":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "scaling distributed transaction processing and recovery based on dependency logging")

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.DB(Databases)