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oai:www.ideals.illinois.edu:2142/81678 2023-07-11 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Zhou, Yuanyuan Chen, Zhifeng 2015-09-25T20:19:59Z 2015-09-25T20:19:59Z 10000-01-01 2005 2005 To address the memory access bottleneck, this dissertation proposes Hanuman, which reformats data dynamically in the database buffer. By adapting data layouts to the changing workload, Hanuman improves the data spatial locality and the processor cache hit ratio accordingly. To determine the best data layout, Hanuman conducts the heuristic cost analysis for candidate layouts and chooses the best layout that minimizes the estimated cache misses. Our result indicates that Hanuman is effective and efficient. Made available in DSpace on 2015-09-25T20:19:59Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3198944.pdf: 3661941 bytes, checksum: 5805fb5acaa0588affbc5629b0826ed7 (MD5) Previous issue date: 2005 Embargo set by: Seth Robbins for item 82959 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs U of I Only 115 p. Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2005. http://hdl.handle.net/2142/81678 (MiAaPQ)AAI3198944 eng Computer Science Optimization of Data Accesses for Database Applications text Computer Science Computer Science University of Illinois at Urbana-Champaign Dissertation Ph.D.