Accelerating phase unwrapping and affine transformations for optical quadrature microscopy using CUDA

Optical Quadrature Microscopy (OQM) is a process which uses phase data to capture information about the sample being studied. OQM is part of an imaging framework developed by the Optical Science Laboratory at Northeastern University. In one particular application of interest, the framework is used to extract phase information from the image of an embryo to determine embryo viability. Phase Unwrapping is the process of reconstructing the real phase shift (propagation delay) of a sample from the measured “wrapped“ representation which is between −π and +π. Unwrapping can be done using the Minimum L P Norm Phase Unwrap algorithm. Images are first preprocessed using an Affine Transform before they are unwrapped. Both of these steps are time consuming and would benefit greatly from parallelization and acceleration. Faster processing would lower many research barriers (in terms of throughpu

Heterogeneous computing with OpenCL 2.0

Heterogeneous Computing with OpenCL 2.0 teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units (APUs). This fully-revised edition includes the latest enhancements in OpenCL 2.0 including: Shared virtual memory to increase programming flexibility and reduce data transfers that consume resources Dynamic parallelism which reduces processor load and avoids bottlenecks Improved imaging support and integration with OpenGL  Designed to work on multiple platfo

Heterogeneous Computing with OpenCL

Heterogeneous Computing with OpenCL teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units (APUs) such as AMD Fusion technology. Designed to work on multiple platforms and with wide industry support, OpenCL will help you more effectively program for a heterogeneous future. Written by leaders in the parallel computing and OpenCL communities, this book will give you hands-on OpenCL experience to address a range of fundamental parallel algorithms. The authors explore