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Title: Scalable FBP decomposition for cone-beam CT reconstruction

Conference ·
 [1];  [2];  [3];  [4];  [5];  [6];  [1];  [1];  [1]
  1. AIST, Japan
  2. University College London (UCL), UK
  3. ORNL
  4. University of Southhampton
  5. University of Southampton, UK
  6. RIKEN Laboratory

Filtered Back-Projection (FBP) is a fundamental compute intense algorithm used in tomographic image reconstruction. Cone-Beam Computed Tomography (CBCT) devices use a cone-shaped X-ray beam, in comparison to the parallel beam used in older CT generations. Distributed image reconstruction of cone-beam datasets typically relies on dividing batches of images into different nodes. This simple input decomposition, however, introduces limits on input/output sizes and scalability.We propose a novel decomposition scheme and reconstruction algorithm for distributed FPB. This scheme enables arbitrarily large input/output sizes, eliminates the redundancy arising in the end-to-end pipeline and improves the scalability by replacing two communication collectives with only one segmented reduction. Finally, we implement the proposed decomposition scheme in a framework that is useful for all current-generation CT devices (7th gen). In our experiments using up to 1024 GPUs, our framework can construct 40963 volumes, for real-world datasets, in under 16 seconds (including I/O).

Research Organization:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
AC05-00OR22725
OSTI ID:
1862116
Resource Relation:
Conference: International Conference for High Performance Computing, Networking, Storage and Analysis (SC '21) - St. Louis, Missouri, United States of America - 11/14/2021 6:00:00 PM-11/19/2021 10:00:00 AM
Country of Publication:
United States
Language:
English