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Mayuresh, K., et al. (2017) ROBUS: Fair Cache Allocation for Data-Parallel Workloads. Proceedings of the 2017 ACM International Conference on Management of Data, Chicago, 14-19 May 2017.

has been cited by the following article:

  • TITLE: Adaptive Cache Allocation with Prefetching Policy over End-to-End Data Processing

    AUTHORS: Hang Qin, Li Zhu

    KEYWORDS: End-to-End, Data Processing, Storage System, Cache, Prefetching

    JOURNAL NAME: Journal of Signal and Information Processing, Vol.8 No.3, July 31, 2017

    ABSTRACT: With the speed gap between storage system access and processor computing, end-to-end data processing has become a bottleneck to improve the total performance of computer systems over the Internet. Based on the analysis of data processing behavior, an adaptive cache organization scheme is proposed with fast address calculation. This scheme can make full use of the characteristics of stack space data access, adopt fast address calculation strategy, and reduce the hit time of stack access. Adaptively, the stack cache can be turned off from beginning to end, when a stack overflow occurs to avoid the effect of stack switching on processor performance. Also, through the instruction cache and the failure behavior for the data cache, a prefetching policy is developed, which is combined with the data capture of the failover queue state. Finally, the proposed method can maintain the order of instruction and data access, which facilitates the extraction of prefetching in the end-to-end data processing.