CuART: Fine-Grained Algebraic Reconstruction Technique for Computed Tomography Images on GPUs

Xiaodong Yu, Hao Wang, Wu Chun Feng, Hao Gong, Guohua Cao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Algebraic reconstruction technique (ART) is an iterative algorithm for computed tomography (CT) image reconstruction. Due to the high computational cost, researchers turn to modern HPC systems with GPUs to accelerate the ART algorithm. However, the existing proposals suffer from inefficient designs of compressed data structure and computational kernel on GPUs. In this paper, we identify the computational patterns in the ART as the product of a sparse matrix (and its transpose) with multiple vectors (SpMV and SpMV-T). Because the implementations with well-tuned libraries, including cuSPARSE, BRC, and CSR5, underperform the expectations, we propose cuART, a complete compression and parallelization solution for the ART-based CT on GPUs. Based on the physical characteristics, i.e., the symmetries in the system matrix, we propose the symmetry-based CSR format (SCSR), which can further compress data storage by removing symmetric but redundant non-zero elements. Leveraging the sparsity patterns of X-ray projection, wetransform the CSR format to multiple dense sub-matrices in SCSR. We then design a transposition-free kernel to optimize the data access for both SpMV and SpMV-T. The experimental results illustrate that our mechanism can reduce memory usage significantly and make practical datasets fit into a single GPU. Our results also illustrate the superior performance of cuART compared to the existing methods on CPU and GPU.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages165-168
Number of pages4
ISBN (Electronic)9781509024520
DOIs
StatePublished - Jul 18 2016
Event16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2016 - Cartagena, Colombia
Duration: May 16 2016May 19 2016

Publication series

NameProceedings - 2016 16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2016

Conference

Conference16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2016
Country/TerritoryColombia
CityCartagena
Period5/16/165/19/16

Keywords

  • Algebraic Reconstruction Technique
  • Computed Tomography
  • GPU
  • Image Reconstruction
  • SpMV
  • SpMV-T

ASJC Scopus subject areas

  • Computer Networks and Communications

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