Paper Info
Title
Accelerating Mutual-Information-Based Linear Registration On The Cell Broadband Engine Processor
Abstract
Emerging multi-core processors are able to accelerate medical imaging applications by exploiting the parallelism available in their algorithms. We have implemented a mutual-information-based 3D linear registration algorithm on the Cell Broadband Engine (TM) processor. By exploiting the highly parallel architecture and its high memory bandwidth, our implementation with two CBE processors can register a pair of 256x256x30 3D images in one second. This implementation is significantly faster than a conventional one on a traditional microprocessor or even faster than a previously reported custom-hardware implementation. In addition to parallelizing the code for multiple cores and organizing the data structure for reducing the amount of the memory traffic, it is also critical to optimize the code for the SIMD pipeline structure. We note that code optimization for the SIMD pipeline alone results in a 4.2x-8.7x acceleration for the computation of small kernels. Further, SIMD optimization alone results in a 4.5x end-end application speedup.
Year
DOI
Venue
2007
10.1109/ICME.2007.4284639
2007 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO, VOLS 1-5
Keywords
Field
DocType
image registration, biomedical image processing, parallel processing
Program optimization,Data structure,Computer science,High memory,Microprocessor,Parallel computing,SIMD,Bandwidth (signal processing),Multi-core processor,Speedup
Conference
Citations 
PageRank 
References 
2
0.42
6
Authors
9
Name
Order
Citations
PageRank
Moriyoshi Ohara12172145.76
Hangu Yeo2306.74
Frank Savino320.42
Giridharan Iyengar428931.57
Leiguang Gong520619.56
Hiroshi Inoue620.42
Hideaki Komatsu741034.00
Vadim Sheinin83810.07
Shahrokh Daijavad913815.84