memory scaling
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2021 ◽  
Vol 31 (11) ◽  
pp. R721-R723
Author(s):  
Carola I. Radulescu ◽  
Samuel J. Barnes

Author(s):  
Xinying Wang ◽  
Cong Xu ◽  
Ke Wang ◽  
Feng Yan ◽  
Dongfang Zhao

2019 ◽  
Vol 214 ◽  
pp. 05018
Author(s):  
Sami Kama ◽  
Charles Leggett ◽  
Scott Snyder ◽  
Vakho Tsulaia

In preparation for Run 3 of the LHC, scheduled to start in 2021, the ATLAS experiment is revising its offline software so as to better take advantage of machines with many cores. A major part of this effort is migrating the software to run as a fully multithreaded application, as this has been shown to significantly improve the memory scaling behavior. This note outlines changes made to the software framework to support this migration.


2017 ◽  
Vol 50 (4) ◽  
pp. 985-993 ◽  
Author(s):  
Ti-Yen Lan ◽  
Jennifer L. Wierman ◽  
Mark W. Tate ◽  
Hugh T. Philipp ◽  
Veit Elser ◽  
...  

Recently, there has been a growing interest in adapting serial microcrystallography (SMX) experiments to existing storage ring (SR) sources. For very small crystals, however, radiation damage occurs before sufficient numbers of photons are diffracted to determine the orientation of the crystal. The challenge is to merge data from a large number of such `sparse' frames in order to measure the full reciprocal space intensity. To simulate sparse frames, a dataset was collected from a large lysozyme crystal illuminated by a dim X-ray source. The crystal was continuously rotated about two orthogonal axes to sample a subset of the rotation space. With the EMC algorithm [expand–maximize–compress; Loh & Elser (2009).Phys. Rev. E,80, 026705], it is shown that the diffracted intensity of the crystal can still be reconstructed even without knowledge of the orientation of the crystal in any sparse frame. Moreover, parallel computation implementations were designed to considerably improve the time and memory scaling of the algorithm. The results show that EMC-based SMX experiments should be feasible at SR sources.


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