Sherman Braganza presented his MS Thesis on Thursday August 14, 2008

Title: Phase Unwrapping on FPGAs and GPUs

Abstract:

Phase unwrapping is the process of converting discontinuous phase data into a
continuous image. This procedure is required by any imaging technology that uses
phase data such as MRI, SAR or OQM microscopy. Such algorithms often take a
significant amount of time to process on a general purpose computer, rendering
it difficult to process large quantities of information. This thesis focuses on
implementing a specific phase unwrapping algorithm known as Minimum $L^P$ norm
unwrapping on a Field Programmable Gate Array (FPGA) and a Graphics Processing
Unit (GPU) for the purpose of speeding it up. The computation required involves
a matrix preconditioner (based on a DCT transform) and a conjugate gradient
calculation along with a few other matrix operations. These functions are
partitioned to run on the host or the accelerator depending on the capabilities
of the accelerator. The tradeoffs between the two platforms is analyzed and
compared to a General Purpose Processor (GPP) in terms of performance,
power and cost.