2026-09-20T05:14:12Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/81815 2023-07-11 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Zilles, Craig Salverda, Pierre M. 2015-09-25T20:20:34Z 2015-09-25T20:20:34Z 10000-01-01 2008 2008 The clustered machines, by contrast, are shown to be inherently capable of matching monolithic machine performance, the penalties imposed by distributed execution notwithstanding. Key to exploiting that potential is knowledge of the critical path through a program. This can be used to achieve a judicious allocation of execution resources to instructions, with performance-critical instructions being shielded from the distributed machine's execution constraints; only the least important instructions, which can tolerate some delay, need be exposed to those constraints. This dissertation develops several novel critical path-aware schemes, and shows that they can deliver performance that is within a few percent of a monolithic machine. It further shows that many aspects of those schemes are stable, both within and across runs of a program, a property which lends them to implementation in a static (offline) context. Made available in DSpace on 2015-09-25T20:20:34Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3314880.pdf: 4474371 bytes, checksum: 19f83be6ddb06c295e3ce14f22b91e2b (MD5) Previous issue date: 2008 Embargo set by: Seth Robbins for item 83096 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 232 p. Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2008. http://hdl.handle.net/2142/81815 (MiAaPQ)AAI3314880 eng Computer Science Principles of Instruction-Level Distributed Processing text Computer Science Computer Science University of Illinois at Urbana-Champaign Dissertation Ph.D.