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Towards Automated Performance Tuning For Complex Workloads

Summary: Introduces M&M, a feedback-based tuner that independently adjusts per-class multiprogramming levels and memory to meet response-time targets despite shared-resource interference. Simulation shows near-target performance for mixed short transactions and long ad hoc joins. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
8373
Venue
VLDB
Year
1994
Pagerank
8.6233649e-05
Overall Rank
2,403 | 83.52%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{brown_vldb94,
        title = {{Towards Automated Performance Tuning For Complex Workloads}},
        author = {Brown, Kurt P. and Mehta, Manish and Carey, Michael J. and Livny, Miron},
        journal = {PVLDB},
        series = {{VLDB} '94},
        year = {1994}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
7 Implementation Techniques For Main Memory Database Systems 1984 SIGMOD 0.00083340894
2,184 Managing Memory to Meet Multiclass Workload Response Time Goals 1993 VLDB 9.0045033e-05
2,360 Dynamic Memory Allocation for Multiple-Query Workloads 1993 VLDB 8.6956893e-05
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