Efficient architectures of heterogeneous fpga-gpu for 3-d medical image compression

Efficient architectures of heterogeneous fpga-gpu for 3-d medical image compression

The advent of development in three-dimensional (3-D) imaging modalities have generated a massive amount of volumetric data in 3-D images such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and ultrasound (US). Existing survey reveals the presence o...

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Main Author: Muharam, Azlan
Format: Thesis
Language:English
English
English
Published: 2019
Subjects:
QA76 Computer software
Online Access:http://eprints.uthm.edu.my/55/1/24p%20AZLAN%20MUHARAM.pdf
http://eprints.uthm.edu.my/55/2/AZLAN%20MUHARAM%20COPYRIGHT%20DECLARATION.pdf
http://eprints.uthm.edu.my/55/3/AZLAN%20MUHARAM%20WATERMARK.pdf
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spelling my-uthm-ep.552021-06-22T03:27:22Z Efficient architectures of heterogeneous fpga-gpu for 3-d medical image compression 2019-04 Muharam, Azlan QA76 Computer software The advent of development in three-dimensional (3-D) imaging modalities have generated a massive amount of volumetric data in 3-D images such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and ultrasound (US). Existing survey reveals the presence of a huge gap for further research in exploiting reconfigurable computing for 3-D medical image compression. This research proposes an FPGA based co-processing solution to accelerate the mentioned medical imaging system. The HWT block implemented on the sbRIO-9632 FPGA board is Spartan 3 (XC3S2000) chip prototyping board. Analysis and performance evaluation of the 3-D images were been conducted. Furthermore, a novel architecture of context-based adaptive binary arithmetic coder (CABAC) is the advanced entropy coding tool employed by main and higher profiles of H.264/AVC. This research focuses on GPU implementation of CABAC and comparative study of discrete wavelet transform (DWT) and without DWT for 3-D medical image compression systems. Implementation results on MRI and CT images, showing GPU significantly outperforming single-threaded CPU implementation. Overall, CT and MRI modalities with DWT outperform in term of compression ratio, peak signal to noise ratio (PSNR) and latency compared with images without DWT process. For heterogeneous computing, MRI images with various sizes and format, such as JPEG and DICOM was implemented. Evaluation results are shown for each memory iteration, transfer sizes from GPU to CPU consuming more bandwidth or throughput. For size 786, 486 bytes JPEG format, both directions consumed bandwidth tend to balance. Bandwidth is relative to the transfer size, the larger sizing will take more latency and throughput. Next, OpenCL implementation for concurrent task via dedicated FPGA. Finding from implementation reveals, OpenCL on batch procession mode with AOC techniques offers substantial results where the amount of logic, area, register and memory increased proportionally to the number of batch. It is because of the kernel will copy the kernel block refer to batch number. Therefore memory bank increased periodically related to kernel block. It was found through comparative study that the tree balance and unroll loop architecture provides better achievement, in term of local memory, latency and throughput. 2019-04 Thesis http://eprints.uthm.edu.my/55/ http://eprints.uthm.edu.my/55/1/24p%20AZLAN%20MUHARAM.pdf text en public http://eprints.uthm.edu.my/55/2/AZLAN%20MUHARAM%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/55/3/AZLAN%20MUHARAM%20WATERMARK.pdf text en validuser phd doctoral Universiti Tun Hussein Onn Malaysia Fakulti Kejuruteraan Elektrik dan Elektronik
institution Universiti Tun Hussein Onn Malaysia
collection UTHM Institutional Repository
language English
English
English
topic QA76 Computer software
spellingShingle QA76 Computer software
Muharam, Azlan
Efficient architectures of heterogeneous fpga-gpu for 3-d medical image compression
description The advent of development in three-dimensional (3-D) imaging modalities have generated a massive amount of volumetric data in 3-D images such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and ultrasound (US). Existing survey reveals the presence of a huge gap for further research in exploiting reconfigurable computing for 3-D medical image compression. This research proposes an FPGA based co-processing solution to accelerate the mentioned medical imaging system. The HWT block implemented on the sbRIO-9632 FPGA board is Spartan 3 (XC3S2000) chip prototyping board. Analysis and performance evaluation of the 3-D images were been conducted. Furthermore, a novel architecture of context-based adaptive binary arithmetic coder (CABAC) is the advanced entropy coding tool employed by main and higher profiles of H.264/AVC. This research focuses on GPU implementation of CABAC and comparative study of discrete wavelet transform (DWT) and without DWT for 3-D medical image compression systems. Implementation results on MRI and CT images, showing GPU significantly outperforming single-threaded CPU implementation. Overall, CT and MRI modalities with DWT outperform in term of compression ratio, peak signal to noise ratio (PSNR) and latency compared with images without DWT process. For heterogeneous computing, MRI images with various sizes and format, such as JPEG and DICOM was implemented. Evaluation results are shown for each memory iteration, transfer sizes from GPU to CPU consuming more bandwidth or throughput. For size 786, 486 bytes JPEG format, both directions consumed bandwidth tend to balance. Bandwidth is relative to the transfer size, the larger sizing will take more latency and throughput. Next, OpenCL implementation for concurrent task via dedicated FPGA. Finding from implementation reveals, OpenCL on batch procession mode with AOC techniques offers substantial results where the amount of logic, area, register and memory increased proportionally to the number of batch. It is because of the kernel will copy the kernel block refer to batch number. Therefore memory bank increased periodically related to kernel block. It was found through comparative study that the tree balance and unroll loop architecture provides better achievement, in term of local memory, latency and throughput.
format Thesis
qualification_name Doctor of Philosophy (PhD.)
qualification_level Doctorate
author Muharam, Azlan
author_facet Muharam, Azlan
author_sort Muharam, Azlan
title Efficient architectures of heterogeneous fpga-gpu for 3-d medical image compression
title_short Efficient architectures of heterogeneous fpga-gpu for 3-d medical image compression
title_full Efficient architectures of heterogeneous fpga-gpu for 3-d medical image compression
title_fullStr Efficient architectures of heterogeneous fpga-gpu for 3-d medical image compression
title_full_unstemmed Efficient architectures of heterogeneous fpga-gpu for 3-d medical image compression
title_sort efficient architectures of heterogeneous fpga-gpu for 3-d medical image compression
granting_institution Universiti Tun Hussein Onn Malaysia
granting_department Fakulti Kejuruteraan Elektrik dan Elektronik
publishDate 2019
url http://eprints.uthm.edu.my/55/1/24p%20AZLAN%20MUHARAM.pdf
http://eprints.uthm.edu.my/55/2/AZLAN%20MUHARAM%20COPYRIGHT%20DECLARATION.pdf
http://eprints.uthm.edu.my/55/3/AZLAN%20MUHARAM%20WATERMARK.pdf
_version_ 1747830517959491584

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