Award Date

1-1-1993

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

Number of Pages

89

Abstract

In this thesis we first investigate the reaching definitions optimization. This compiler optimization collects and stores information about where a variable is defined and how long that definition of the variable stays alive before it is redefined. We compare the old iterative solution to a new algorithm that uses the partialout concept. The partialout solution decreases execution time by eliminating the multiple passes required in the iterative solution. Currently, compilers that find a data dependence between two statements in a loop do not parallelize the loop. Next we investigate automatic parallelism for these loops by breaking the loop into a set of smaller loops, each of which contains no dependencies and thus can be executed in parallel. Finally, we introduce a set of algorithms for optimal processor utilization. The algorithms split the loop into a sequential series of parallel blocks, each block executing in parallel and utilizing the optimal number of processors possible.

Keywords

Algorithms; Automatic; Optimal; Optimization; Parallelism; Processor; Utilization

Controlled Subject

Computer science

File Format

pdf

File Size

2252.8 KB

Degree Grantor

University of Nevada, Las Vegas

Language

English

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