Parallelization of SIFT on Rigel

With the trend towards parallel processing in computing, interest is developing in enabling workloads to be done at faster speeds to enable new usage models. SIFT is an algorithm for image detection and can be used for a variety of purposes. It collects key-point features that are invariant to changes in lighting, orientation and affine transforms. We ported the SIFT algorithm to the many-core architecture Rigel and studied the amount of speedup that can be gained by parallelizing the algorithm. Our results showed the algorithm to provide a speedup of 75x when parallelized over 128 cores.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2011

Author dc:creator

• Hussain, Ali A.

Contributors dc:contributor

• Patel, Sanjay J.

• Scale-Invariant Feature Transform (SIFT)
• Rigel
• Parallelization
• Image recognition

Statement dc:rights

• Copyright 2011 Ali A. Hussain

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/24154

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/24154