Title
EMBIRA: An Accelerator for Model-Based Iterative Reconstruction.
Abstract
Tomographic reconstruction, which involves computing a 3-D volume from its 2-D projections, is an important problem in imaging with wide-ranging applications, including medical scanners, electron microscopy, nondestructive testing, and transportation security. Model-based iterative reconstruction (MBIR) is a popular approach to 3-D reconstruction that has demonstrated the state-of-the-art reconstruction quality on several applications, and has been deployed in commercial healthcare systems. However, software implementations of MBIR on commodity general-purpose processors demonstrate poor performance due to its high compute and data requirements and cache unfriendly data access patterns. In this paper, we develop an efficient MBIR accelerator (EMBIRA) that achieves significant performance and energy improvement over software implementations. EMBIRA utilizes arrays of three types of specialized processing elements that match MBIR’s computation patterns, and is further operated as a two-level nested pipeline to fully exploit the parallelism present in the algorithm. Another important source from which EMBIRA derives its efficiency is by constraining the sequence in which voxels1 in the 3-D volume are reconstructed. This enables better data reuse within the accelerator, thereby significantly reducing the number of off-chip memory accesses. To demonstrate the benefits of EMBIRA, we implemented a prototype on an Altera DE5 field-programmable gate array (FPGA) platform that includes an Altera Stratix V GX FPGA and DDR3 memory. Our implementation of EMBIRA, operating at 165 MHz, achieved $51.8\\times $ ( $5.8\\times $ ) improvement in performance, and $355\\times $ ( $199\\times $ ) improvement in energy, compared with optimized sequential (multithreaded) software implementations on a 48-core 2.3-GHz AMD Opteron-based server.1Each location in the 3-D volume represents a voxel. It is analogous to a pixel in a 2-D image.
Year
DOI
Venue
2016
10.1109/TVLSI.2016.2551204
IEEE Trans. VLSI Syst.
Keywords
Field
DocType
Image reconstruction,Software,Tomography,Arrays,Parallel processing,Very large scale integration
Iterative reconstruction,Stratix,Tomographic reconstruction,Computer science,Cache,Field-programmable gate array,Electronic engineering,Real-time computing,Gate array,Software,Very-large-scale integration
Journal
Volume
Issue
ISSN
24
11
1063-8210
Citations 
PageRank 
References 
0
0.34
13
Authors
6
Name
Order
Citations
PageRank
Junshi Liu100.34
Swagath Venkataramani263139.33
S. V. Venkatakrishnan31138.59
Yun Pan414.45
Charles A. Bouman52740473.62
Anand Raghunathan65375415.27