Developing a Massively Parallel Forward Projection Radiography Model for Large-Scale Industrial Applications
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
This project utilizes Graphics Processing Units (GPUs) to compute radiograph simulations for arbitrary objects. The generation of radiographs, also known as the forward projection imaging model, is computationally intensive and not widely utilized. The goal of this research is to develop a massively parallel algorithm that can compute forward projections for objects with a trillion voxels (3D pixels). To achieve this end, the data are divided into blocks that can each t into GPU memory. The forward projected image is also divided into segments to allow for future parallelization and to avoid needless computations.
- Research Organization:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE; DHS
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 1171557
- Report Number(s):
- SAND2014-17037R; 536968
- Country of Publication:
- United States
- Language:
- English
Similar Records
TH-E-18A-01: Developments in Monte Carlo Methods for Medical Imaging
A massively parallel and scalable multi-CPU material point method
High performance graphics processor based computed tomography reconstruction algorithms for nuclear and other large scale applications.
Journal Article
·
Sun Jun 15 00:00:00 EDT 2014
· Medical Physics
·
OSTI ID:1171557
+1 more
A massively parallel and scalable multi-CPU material point method
Conference
·
Wed Jul 01 00:00:00 EDT 2020
·
OSTI ID:1171557
+7 more
High performance graphics processor based computed tomography reconstruction algorithms for nuclear and other large scale applications.
Technical Report
·
Sun Sep 01 00:00:00 EDT 2013
·
OSTI ID:1171557