Open Access

High Speed 3D Tomography on CPU, GPU, and FPGA

  • Nicolas GAC1, 2Email author,
  • Stéphane Mancini1,
  • Michel Desvignes1 and
  • Dominique Houzet1
EURASIP Journal on Embedded Systems20092008:930250

DOI: 10.1155/2008/930250

Received: 1 March 2008

Accepted: 12 November 2008

Published: 18 January 2009


Back-projection (BP) is a costly computational step in tomography image reconstruction such as positron emission tomography (PET). To reduce the computation time, this paper presents a pipelined, prefetch, and parallelized architecture for PET BP (3PA-PET). The key feature of this architecture is its original memory access strategy, masking the high latency of the external memory. Indeed, the pattern of the memory references to the data acquired hinders the processing unit. The memory access bottleneck is overcome by an efficient use of the intrinsic temporal and spatial locality of the BP algorithm. A loop reordering allows an efficient use of general purpose processor's caches, for software implementation, as well as the 3D predictive and adaptive cache (3D-AP cache), when considering hardware implementations. Parallel hardware pipelines are also efficient thanks to a hierarchical 3D-AP cache: each pipeline performs a memory reference in about one clock cycle to reach a computational throughput close to 100%. The 3PA-PET architecture is prototyped on a system on programmable chip (SoPC) to validate the system and to measure its expected performances. Time performances are compared with a desktop PC, a workstation, and a graphic processor unit (GPU).

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Authors’ Affiliations

Grenoble-Images-Parole-Signal-Automatique Laboratoire (GIPSA-lab), Grenoble Institute of Technology (INPG)
Equipes Traitement des Images et du Signal (ETIS), Centre National de la Recherche Scientifique (CNRS), Ecole Nationale Sup_rieure de l'Electronique et de ses Applications (ENSEA), Université de Cergy-Pontoise


© Nicolas GAC et al. 2008

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.