Director of Research (if dissertation) or Advisor (if thesis)
Patel, Sanjay J.
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Scale-Invariant Feature Transform (SIFT)
Rigel
Parallelization
Image recognition
Abstract
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.
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