Publication Date

Spring 5-20-2016

Degree Type

Master's Project

Degree Name

Master of Science (MS)

Department

Computer Science

First Advisor

Chris Pollett

Second Advisor

Sami Khuri

Third Advisor

Thomas Austin

Abstract

One of the main requirements of internet search engines is the ability to retrieve relevant results with faster response times. Yioop is an open source search engine designed and developed in PHP by Dr. Chris Pollett. The goal of this project is to explore the possibilities of enhancing the performance of Yioop by substituting resource-intensive existing PHP functions with C based native PHP extensions and the parallel data processing technology OpenCL. OpenCL leverages the Graphical Processing Unit (GPU) of a computer system for performance improvements.

Some of the critical functions in search engines are resource-intensive in terms of processing power, memory, and I/O usage. The processing times vary based on the complexity and magnitude of data involved. This project involves different phases such as identifying critical resource intensive functions, initially replacing such methods with PHP Extensions, and eventually experimenting with OpenCL code. We also ran performance tests to measure the reduction in processing times. From our results, we concluded that PHP Extensions and OpenCL processing resulted in performance improvements.

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