Hawk: the image reconstruction package for coherent X-ray diffractive imaging

2010 ◽  
Vol 43 (6) ◽  
pp. 1535-1539 ◽  
Author(s):  
Filipe R. N. C. Maia ◽  
Tomas Ekeberg ◽  
David van der Spoel ◽  
Janos Hajdu
Keyword(s):  
Open Source ◽  
Graphics Processing Units ◽  
Rapid Development ◽  
Three Dimensional ◽  
Processing Unit ◽  
Diffractive Imaging ◽  
X Ray ◽  
Two Dimensional Image ◽  
Central Processing ◽  
Diffraction Patterns

The past few years have seen a tremendous growth in the field of coherent X-ray diffractive imaging, in large part due to X-ray free-electron lasers which provide a peak brilliance billions of times higher than that of synchrotrons. However, this rapid development in terms of hardware has not been matched on the software side. The release ofHawkis intended to close this gap. To the authors' knowledgeHawkis the first publicly available and fully open source software program for reconstructing images from continuous diffraction patterns. The software handles all steps leading from a raw diffraction pattern to a reconstructed two-dimensional image including geometry determination, background correction, masking and phasing. It also includes preliminary three-dimensional support and support for graphics processing units using the Compute Unified Device Architecture, which speeds up processing by orders of magnitude compared to a single central processing unit.Hawkimplements numerous algorithms and is easily extended. This, in combination with its open-source licence, provides a platform for other groups to test, develop and distribute their own algorithms.Hawkis available under the GNU General Public License from http://xray.bmc.uu.se/hawk.

scholarly journals Hard X-ray polarizer to enable simultaneous three-dimensional nanoscale imaging of magnetic structure and lattice strain

2016 ◽  
Vol 23 (5) ◽  
pp. 1210-1215 ◽  
Author(s):  
Jonathan Logan ◽  
Ross Harder ◽  
Luxi Li ◽  
Daniel Haskel ◽  
Pice Chen ◽  
...  
Keyword(s):  
Magnetic Circular Dichroism ◽  
Three Dimensional ◽  
Control Sample ◽  
Magnetic Ordering ◽  
X Rays ◽  
Diffractive Imaging ◽  
X Ray ◽  
Coherent Diffractive Imaging ◽  
Diffraction Patterns ◽  
A New Technique

Recent progress in the development of dichroic Bragg coherent diffractive imaging, a new technique for simultaneous three-dimensional imaging of strain and magnetization at the nanoscale, is reported. This progress includes the installation of a diamond X-ray phase retarder at beamline 34-ID-C of the Advanced Photon Source. The performance of the phase retarder for tuning X-ray polarization is demonstrated with temperature-dependent X-ray magnetic circular dichroism measurements on a gadolinium foil in transmission and on a Gd5Si2Ge2crystal in diffraction geometry with a partially coherent, focused X-ray beam. Feasibility tests for dichroic Bragg coherent diffractive imaging are presented. These tests include (1) using conventional Bragg coherent diffractive imaging to determine whether the phase retarder introduces aberrations using a nonmagnetic gold nanocrystal as a control sample, and (2) collecting coherent diffraction patterns of a magnetic Gd5Si2Ge2nanocrystal with left- and right-circularly polarized X-rays. Future applications of dichroic Bragg coherent diffractive imaging for the correlation of strain and lattice defects with magnetic ordering and inhomogeneities are considered.

An Accelerated 3D Navier–Stokes Solver for Flows in Turbomachines

2010 ◽  
Vol 133 (2) ◽  
Author(s):  
Tobias Brandvik ◽  
Graham Pullan
Keyword(s):  
Graphics Processing Units ◽  
Three Dimensional ◽  
Navier Stokes ◽  
Linear Scaling ◽  
Test Case ◽  
Processing Unit ◽  
Central Processing ◽  
Order Of Magnitude ◽  
Graphics Processing ◽  
Good Agreement

A new three-dimensional Navier–Stokes solver for flows in turbomachines has been developed. The new solver is based on the latest version of the Denton codes but has been implemented to run on graphics processing units (GPUs) instead of the traditional central processing unit. The change in processor enables an order-of-magnitude reduction in run-time due to the higher performance of the GPU. The scaling results for a 16 node GPU cluster are also presented, showing almost linear scaling for typical turbomachinery cases. For validation purposes, a test case consisting of a three-stage turbine with complete hub and casing leakage paths is described. Good agreement is obtained with previously published experimental results. The simulation runs in less than 10 min on a cluster with four GPUs.

An Accelerated 3D Navier-Stokes Solver for Flows in Turbomachines

2009 ◽  
Author(s):  
Tobias Brandvik ◽  
Graham Pullan
Keyword(s):  
Graphics Processing Units ◽  
Three Dimensional ◽  
Navier Stokes ◽  
Linear Scaling ◽  
Test Case ◽  
Processing Unit ◽  
Central Processing ◽  
Order Of Magnitude ◽  
Graphics Processing ◽  
Good Agreement

A new three-dimensional Navier-Stokes solver for flows in turbomachines has been developed. The new solver is based on the latest version of the Denton codes, but has been implemented to run on Graphics Processing Units (GPUs) instead of the traditional Central Processing Unit (CPU). The change in processor enables an order-of-magnitude reduction in run-time due to the higher performance of the GPU. Scaling results for a 16 node GPU cluster are also presented, showing almost linear scaling for typical turbomachinery cases. For validation purposes, a test case consisting of a three-stage turbine with complete hub and casing leakage paths is described. Good agreement is obtained with previously published experimental results. The simulation runs in less than 10 minutes on a cluster with four GPUs.

scholarly journals Accelerating 3D Medical Image Segmentation by Adaptive Small-Scale Target Localization

2021 ◽  
Vol 7 (2) ◽  
pp. 35
Author(s):  
Boris Shirokikh ◽  
Alexey Shevtsov ◽  
Alexandra Dalechina ◽  
Egor Krivov ◽  
Valery Kostjuchenko ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Graphics Processing Units ◽  
Medical Image ◽  
State Of The Art ◽  
Three Dimensional ◽  
Medical Image Segmentation ◽  
Small Scale ◽  
Processing Unit ◽  
Central Processing ◽  
Lung Cancer Diagnosis

The prevailing approach for three-dimensional (3D) medical image segmentation is to use convolutional networks. Recently, deep learning methods have achieved human-level performance in several important applied problems, such as volumetry for lung-cancer diagnosis or delineation for radiation therapy planning. However, state-of-the-art architectures, such as U-Net and DeepMedic, are computationally heavy and require workstations accelerated with graphics processing units for fast inference. However, scarce research has been conducted concerning enabling fast central processing unit computations for such networks. Our paper fills this gap. We propose a new segmentation method with a human-like technique to segment a 3D study. First, we analyze the image at a small scale to identify areas of interest and then process only relevant feature-map patches. Our method not only reduces the inference time from 10 min to 15 s but also preserves state-of-the-art segmentation quality, as we illustrate in the set of experiments with two large datasets.

scholarly journals Considerations for three-dimensional image reconstruction from experimental data in coherent diffractive imaging

IUCrJ ◽  
2018 ◽  
Vol 5 (5) ◽  
pp. 531-541 ◽  
Author(s):  
Ida V. Lundholm ◽  
Jonas A. Sellberg ◽  
Tomas Ekeberg ◽  
Max F. Hantke ◽  
Kenta Okamoto ◽  
...  
Keyword(s):  
Experimental Data ◽  
Phase Retrieval ◽  
Three Dimensional ◽  
Simulated Data ◽  
High Repetition Rate ◽  
Central Feature ◽  
Diffractive Imaging ◽  
X Ray ◽  
Background Removal ◽  
Diffraction Patterns

Diffraction before destruction using X-ray free-electron lasers (XFELs) has the potential to determine radiation-damage-free structures without the need for crystallization. This article presents the three-dimensional reconstruction of the Melbournevirus from single-particle X-ray diffraction patterns collected at the LINAC Coherent Light Source (LCLS) as well as reconstructions from simulated data exploring the consequences of different kinds of experimental sources of noise. The reconstruction from experimental data suffers from a strong artifact in the center of the particle. This could be reproduced with simulated data by adding experimental background to the diffraction patterns. In those simulations, the relative density of the artifact increases linearly with background strength. This suggests that the artifact originates from the Fourier transform of the relatively flat background, concentrating all power in a central feature of limited extent. We support these findings by significantly reducing the artifact through background removal before the phase-retrieval step. Large amounts of blurring in the diffraction patterns were also found to introduce diffuse artifacts, which could easily be mistaken as biologically relevant features. Other sources of noise such as sample heterogeneity and variation of pulse energy did not significantly degrade the quality of the reconstructions. Larger data volumes, made possible by the recent inauguration of high repetition-rate XFELs, allow for increased signal-to-background ratio and provide a way to minimize these artifacts. The anticipated development of three-dimensional Fourier-volume-assembly algorithms which are background aware is an alternative and complementary solution, which maximizes the use of data.

scholarly journals A Distributed GPU-Based Framework for Real-Time 3D Volume Rendering of Large Astronomical Data Cubes

2012 ◽  
Vol 29 (3) ◽  
pp. 340-351 ◽  
Author(s):  
A. H. Hassan ◽  
C. J. Fluke ◽  
D. G. Barnes
Keyword(s):  
Real Time ◽  
Volume Rendering ◽  
Graphics Processing Units ◽  
Three Dimensional ◽  
Data Cube ◽  
Processing Unit ◽  
Ray Casting ◽  
Data Cubes ◽  
Central Processing ◽  
3D Volume

AbstractWe present a framework to volume-render three-dimensional data cubes interactively using distributed ray-casting and volume-bricking over a cluster of workstations powered by one or more graphics processing units (GPUs) and a multi-core central processing unit (CPU). The main design target for this framework is to provide an in-core visualization solution able to provide three-dimensional interactive views of terabyte-sized data cubes. We tested the presented framework using a computing cluster comprising 64 nodes with a total of 128 GPUs. The framework proved to be scalable to render a 204 GB data cube with an average of 30 frames per second. Our performance analyses also compare the use of NVIDIA Tesla 1060 and 2050 GPU architectures and the effect of increasing the visualization output resolution on the rendering performance. Although our initial focus, as shown in the examples presented in this work, is volume rendering of spectral data cubes from radio astronomy, we contend that our approach has applicability to other disciplines where close to real-time volume rendering of terabyte-order three-dimensional data sets is a requirement.

2D X-ray diffraction and molecular modelling of the crystalline structure of polyesters under uniaxial stress

2021 ◽  
pp. 096739112199822
Author(s):  
Ahmed I Abou-Kandil ◽  
Gerhard Goldbeck
Keyword(s):  
Crystalline Structure ◽  
Molecular Modelling ◽  
Three Dimensional ◽  
Uniaxial Stress ◽  
X Ray Diffraction ◽  
X Ray ◽  
Wide Range ◽  
Modelling Techniques ◽  
Diffraction Patterns

Studying the crystalline structure of uniaxially and biaxially drawn polyesters is of great importance due to their wide range of applications. In this study, we shed some light on the behaviour of PET and PEN under uniaxial stress using experimental and molecular modelling techniques. Comparing experiment with modelling provides insights into polymer crystallisation with extended chains. Experimental x-ray diffraction patterns are reproduced by means of models of chains sliding along the c-axis leading to some loss of three-dimensional order, i.e. moving away from the condition of perfect register of the fully extended chains in triclinic crystals of both PET and PEN. This will help us understand the mechanism of polymer crystallisation under uniaxial stress and the appearance of mesophases in some cases as discussed herein.

scholarly journals FEM using projection of physical properties suitable for movement modeling and optimization processes

2020 ◽  
Vol 39 (5) ◽  
pp. 1185-1199
Author(s):  
Baptiste Ristagno ◽  
Dominique Giraud ◽  
Julien Fontchastagner ◽  
Denis Netter ◽  
Noureddine Takorabet ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Transient State ◽  
Mathematical Function ◽  
Processing Unit ◽  
Time Saving ◽  
Content Type ◽  
Central Processing ◽  
Cpu Time ◽  
Simple Geometry ◽  
Evaluation Time

Purpose Optimization processes and movement modeling usually require a high number of simulations. The purpose of this paper is to reduce global central processing unit (CPU) time by decreasing each evaluation time. Design Methodology Approach Remeshing the geometry at each iteration is avoided in the proposed method. The idea consists in using a fixed mesh on which functions are projected to represent geometry and supply. Findings Results are very promising. CPU time is reduced for three dimensional problems by almost a factor two, keeping a low relative deviation from usual methods. CPU time saving is performed by avoiding meshing step and also by a better initialization of iterative resolution. Optimization, movement modeling and transient-state simulation are very efficient and give same results as usual finite element method. Research Limitations Implications The method is restricted to simple geometry owing to the difficulty of finding spatial mathematical function describing the geometry. Moreover, a compromise between imprecision, caused by the boundary evaluation, and time saving must be found. Originality Value The method can be applied to optimize rotating machines design. Moreover, movement modeling is performed by shifting functions corresponding to moving parts.

scholarly journals Comparative study of the implementation of the Lagrange interpolation algorithm on GPU and CPU using CUDA to compute the density of a material at different temperatures

2021 ◽  
Vol 119 ◽  
pp. 07002
Author(s):  
Youness Rtal ◽  
Abdelkader Hadjoudja
Keyword(s):  
Parallel Computing ◽  
Graphics Processing Units ◽  
Lagrange Interpolation ◽  
Polynomial Interpolation ◽  
Programming Model ◽  
Interpolation Method ◽  
Processing Unit ◽  
Central Processing ◽  
Computational Performance ◽  
Different Temperatures

Graphics Processing Units (GPUs) are microprocessors attached to graphics cards, which are dedicated to the operation of displaying and manipulating graphics data. Currently, such graphics cards (GPUs) occupy all modern graphics cards. In a few years, these microprocessors have become potent tools for massively parallel computing. Such processors are practical instruments that serve in developing several fields like image processing, video and audio encoding and decoding, the resolution of a physical system with one or more unknowns. Their advantages: faster processing and consumption of less energy than the power of the central processing unit (CPU). In this paper, we will define and implement the Lagrange polynomial interpolation method on GPU and CPU to calculate the sodium density at different temperatures Ti using the NVIDIA CUDA C parallel programming model. It can increase computational performance by harnessing the power of the GPU. The objective of this study is to compare the performance of the implementation of the Lagrange interpolation method on CPU and GPU processors and to deduce the efficiency of the use of GPUs for parallel computing.

The Atomic Order in Guinier-Preston Zones of Aluminum-Silver Alloys

1963 ◽  
Vol 7 ◽  
pp. 1-13 ◽  
Author(s):  
Volkmar Gerold ◽  
Heinz Auer ◽  
Winfried Merz
Keyword(s):  
Room Temperature ◽  
Three Dimensional ◽  
Miscibility Gap ◽  
X Rays ◽  
Atomic Order ◽  
Zone Size ◽  
X Ray ◽  
Angle Scattering ◽  
Diffraction Patterns ◽  
Step Quenching

AbstractThe formation of the spherical Guinier—Preston zones in an aluminum-silver alloy is governed by a metastable miscibility gap, which consists of two different sections. The lower section occurs below 170°C (η state), the higher section up to 420°C (∊ state). The zones in the two sections differ in their silver concentration and in their atomic order. To prove the change in order, a combination of X-ray small-angle scattering and electric resistivity measurements was used. As the resistivity depends on the zone size and the atomic order, the change in order can be found when the zone size is known. This size was measured by the X-ray technique. To complete the results, X-rays ingle-crystal diffraction patterns with monochromatic radiation were taken at different stages. According to these patterns, three different states must be distinguished.The η′ state exists at room temperature after quenching from 550°C. The silver atoms prefer a layered arrangement in the zones, which is not very stable. It is destroyed after short annealings above 100°C. The η state is developed during annealing below 170°C. A three-dimensional atomic order is built up with increasing zone size, which results in a marked decrease in the resistivity. For the ∊ state (above 170°C), a nearly random atomic distribution exists. Step-quenching experiments prove that the ordered η state can also be developed at room temperature.

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