Publication
Title
Memory access optimization for iterative tomography on many-core architectures
Author
Abstract
Iterative tomographic reconstruction methods, de- spite their virtues, are known to be slow compared to analytic reconstruction methods, mainly because of the computationally very intensive forward and backward projection operations. By relying on many-core architectures with large vector registers, modern high performance computing (HPC) systems can offer relief. However, to optimally benefit from such systems, the peak performance of the algorithms should not be bound by the memory bandwidth. In this work, a strategy is proposed that improves the performance of the tomographic forward projection by optimizing its memory accesses. Data locality is exploited to hide data access latency and knowledge of the cache architecture is used to optimally distribute the projection operation over many computing cores. Experiments performed on the recently introduced Intel R Xeon Phi TM architecture confirm a substantial boost in projection performance.
Language
English
Source (book)
The 12th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine
Publication
2013
Volume/pages
(2013) , p. 364-367
Full text (open access)
UAntwerpen
Faculty/Department
Research group
Project info
Image reconstruction for in situ Computed Tomography
Quantitative tomographic segmentation of magnetic resonance images
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Record
Identifier
Creation 05.11.2014
Last edited 07.10.2022
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