scholarly journals HIGH-PERFORMANCE COMPUTING FOR THE STUDY OF EARTH AND ENVIRONMENTAL SCIENCE MATERIALS USING SYNCHROTRON X-RAY COMPUTED MICROTOMOGRAPHY

Author(s):  
HUAN FENG ◽  
KEITH W. JONES ◽  
MICHAEL MCGUIGAN ◽  
GORDON J. SMITH ◽  
JOHN SPILETIC
2020 ◽  
Vol 53 (5) ◽  
pp. 1404-1413
Author(s):  
Vincent Favre-Nicolin ◽  
Gaétan Girard ◽  
Steven Leake ◽  
Jerome Carnis ◽  
Yuriy Chushkin ◽  
...  

The open-source PyNX toolkit has been extended to provide tools for coherent X-ray imaging data analysis and simulation. All calculations can be executed on graphical processing units (GPUs) to achieve high-performance computing speeds. The toolkit can be used for coherent diffraction imaging (CDI), ptychography and wavefront propagation, in the far- or near-field regime. Moreover, all imaging operations (propagation, projections, algorithm cycles…) can be implemented in Python as simple mathematical operators, an approach which can be used to easily combine basic algorithms in a tailored chain. Calculations can also be distributed to multiple GPUs, e.g. for large ptychography data sets. Command-line scripts are available for on-line CDI and ptychography analysis, either from raw beamline data sets or using the coherent X-ray imaging data format.


MRS Bulletin ◽  
1997 ◽  
Vol 22 (10) ◽  
pp. 5-6
Author(s):  
Horst D. Simon

Recent events in the high-performance computing industry have concerned scientists and the general public regarding a crisis or a lack of leadership in the field. That concern is understandable considering the industry's history from 1993 to 1996. Cray Research, the historic leader in supercomputing technology, was unable to survive financially as an independent company and was acquired by Silicon Graphics. Two ambitious new companies that introduced new technologies in the late 1980s and early 1990s—Thinking Machines and Kendall Square Research—were commercial failures and went out of business. And Intel, which introduced its Paragon supercomputer in 1994, discontinued production only two years later.During the same time frame, scientists who had finished the laborious task of writing scientific codes to run on vector parallel supercomputers learned that those codes would have to be rewritten if they were to run on the next-generation, highly parallel architecture. Scientists who are not yet involved in high-performance computing are understandably hesitant about committing their time and energy to such an apparently unstable enterprise.However, beneath the commercial chaos of the last several years, a technological revolution has been occurring. The good news is that the revolution is over, leading to five to ten years of predictable stability, steady improvements in system performance, and increased productivity for scientific applications. It is time for scientists who were sitting on the fence to jump in and reap the benefits of the new technology.


Author(s):  
I.V. Yazynina ◽  
◽  
E.V. Shelyago ◽  
A.A. Abrosimov ◽  
N.E. Grachev ◽  
...  

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