2026-09-19T02:36:19Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/24154 2023-07-10 col_2142_5131 col_2142_8888 com_2142_5130 com_2142_8887 com_2142_234

2011-05-25T14:51:09Z Patel, Sanjay J. Hussain, Ali A. 2011-05-25T14:51:09Z 2011-05-25T14:51:09Z 2011-05 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. Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2011-02-25T14:51:50Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 2 thesis.tar.gz: 204669 bytes, checksum: 51f6d4eff4f8e4820d0b512156b03a3d (MD5) Hussain_Ali.pdf: 164111 bytes, checksum: 02bc2ffa16dcf3930854df65598575e9 (MD5) Made available in DSpace on 2011-05-25T14:51:09Z (GMT). No. of bitstreams: 3 Hussain_Ali.pdf: 164111 bytes, checksum: 02bc2ffa16dcf3930854df65598575e9 (MD5) license.txt: 4062 bytes, checksum: 3198d0b6b4dc97d70b2d7b028ca36574 (MD5) thesis.tar.gz: 204669 bytes, checksum: 51f6d4eff4f8e4820d0b512156b03a3d (MD5) http://hdl.handle.net/2142/24154 en Copyright 2011 Ali A. Hussain Scale-Invariant Feature Transform (SIFT) Rigel Parallelization Image recognition Parallelization of SIFT on Rigel Electrical & Computer Eng 1933 Electrical & Computer Engr 1200 University of Illinois at Urbana-Champaign Thesis M.S. MS:Electr & Computer Eng-UIUC 10KS1200MS