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A streaming multi-GPU implementation of image simulation algorithms for scanning transmission electron microscopy

Overview of attention for article published in Advanced Structural and Chemical Imaging, October 2017
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Title
A streaming multi-GPU implementation of image simulation algorithms for scanning transmission electron microscopy
Published in
Advanced Structural and Chemical Imaging, October 2017
DOI 10.1186/s40679-017-0048-z
Pubmed ID
Authors

Alan Pryor, Colin Ophus, Jianwei Miao

Abstract

Simulation of atomic-resolution image formation in scanning transmission electron microscopy can require significant computation times using traditional methods. A recently developed method, termed plane-wave reciprocal-space interpolated scattering matrix (PRISM), demonstrates potential for significant acceleration of such simulations with negligible loss of accuracy. Here, we present a software package called Prismatic for parallelized simulation of image formation in scanning transmission electron microscopy (STEM) using both the PRISM and multislice methods. By distributing the workload between multiple CUDA-enabled GPUs and multicore processors, accelerations as high as 1000 × for PRISM and 15 × for multislice are achieved relative to traditional multislice implementations using a single 4-GPU machine. We demonstrate a potentially important application of Prismatic, using it to compute images for atomic electron tomography at sufficient speeds to include in the reconstruction pipeline. Prismatic is freely available both as an open-source CUDA/C++ package with a graphical user interface and as a Python package, PyPrismatic.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 107 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Unknown 106 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 27%
Researcher 16 15%
Student > Bachelor 11 10%
Student > Master 9 8%
Student > Doctoral Student 4 4%
Other 14 13%
Unknown 24 22%
Readers by discipline Count As %
Materials Science 44 41%
Physics and Astronomy 15 14%
Engineering 8 7%
Computer Science 3 3%
Biochemistry, Genetics and Molecular Biology 1 <1%
Other 7 7%
Unknown 29 27%