Principles of Instruction-Level Distributed Processing

232 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 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.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD