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Alez
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#1 Project Information

Unread post by Alez » Sun Jan 29, 2017 12:29 am

Find project here

About XANSONS for COD
XANSONS for COD is a research project aimed to create an open access database of simulated x-ray and neutron powder diffraction patterns for nanocrystalline phase of the materials presented in the Crystallography Open Database (COD). You can participate by downloading and running a free program on your computer.

The alpha-testing of this project is over. The project is on long-term maintenance now. It will be restarted in the summer of 2017. All the results obtained before the restart will likely be lost.

This project uses original open source (GPLv3 license) software XaNSoNS (X-ray and Neutron Scattering on Nanoscale Structures) to simulate the diffraction patterns on CPU and GPU.

XANSONS for COD is a privately managed BOINC project supported by the Russian Foundation for Basic Research (project RFBR #15-07-07901-a).

Scientific Problem
The conventional technique used to recover the structural properties of the crystalline samples by their powder diffraction pattern is the Rietveld refinement method. In this method, the theoretical powder diffraction pattern is refined until it fits the experimental one. The computation of the angles and intensities of the Bragg peaks can be made almost instantaneously in the approximation of the infinite size of the crystallite. To adjust for the finite size of the crystallites in the samples or finite resolution of the measurement device, these peaks are broadened artificially with the broadening function (usually Gaussian). This artificial broadening works great until the size of the crystallite in the sample is something below few tens of nanometers. For the such small crystallites, it is very hard to get the right broadening function which works fine for all Bragg peaks. Fortunately, for the such small crystallites, it is not a problem to calculate the powder diffraction patterns using the Debye equation (with the distance-histogram approximation, such as that proposed by Marcin Wojdyr and implemented in his Debyer code). This project is aimed to calculate the x-ray and neutron powder diffraction patterns for the nanocrystallites with the size varying from 6 nm to 30 nm for the most of the entries of the Crystallography Open Database. The obtained database may simplify the diagnostics of the nanocrystalline samples and complement the Full Profile Search Match method in the crystallite size analysis of the nanocrystalline samples.

In addition to the above, the calculation of the powder diffraction pattern using the Debye equation allows to account the lattice defects such as site vacancies, atom replacements and displacements. So, if the Crystallography Information File (CIF) for the given structure provides the site occupancy numbers and atomic displacement parameters, the application will use them to calculate the diffraction pattern.

System Requirements

Supported operating systems:

Windows 7 SP1 64-bit and above. Visual C++ Redistributable Packages for Visual Studio 2013 are required (64-bit version).
OS X 10.9.5 and above (including macOS).
64-bit Linux with kernel 3.16 and above.

Supported GPUs:

Nvidia GPU with CUDA Compute Capability 1.3 and above (Windows, Linux) or 2.0 and above (OS X/macOS) with at least 1GB of memory (GDDR5 memory is recommended). Driver version 340.21 and above (Windows, Linux) or CUDA Driver for MAC version 7.0.29 and above (OS X/macOS).
AMD GPU with OpenCL 1.2+ support with at least 1GB of memory (GDDR5 memory is recommended).
Intel GPU with OpenCL 1.2+ support (HD graphics 5xxx/5xx and above or Intel Iris are highly recommended, see Important Notes below).

Important Notes

Some antivirus software may place the executables into quarantine as unknown (and therefore suspicious) files. To prevent this from happening, disable blocking of unknown files in the antivirus preferences (e.g. in Avast disable CyberCapture feature). When BOINC client will download the executables, you can manually scan the BOINC data directory (C:\ProgramData\BOINC\ by default) for viruses. After that, the disabled antivirus functionality may be re-enabled again.

The task progress displaying in the BOINC manager is incorrect for now. This will be fixed by the time of the release. The tasks vary greatly by the computational time. Some tasks can be completed within a second but some require about 10 minutes to complete even on the modern CPU.

The algorithm which solves the problem on GPU requires high memory bandwidth and high memory read/write performance. It uses 64-bit integer atomic functions on Nvidia and AMD GPUs and emulates them on Intel GPUs. Therefore, for the tasks of this project, the GPUs with GDDR3 memory perform significantly slower than the GPUs with GDDR5 memory. For the integrated Intel GPUs below 8th generation (HD graphics 4xxx or older) and integrated AMD GPUs, the performance may be even slower than for the CPU. If you'll notice the very slow GPU performance, disable it in project preferences in your account page.
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Alez
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#2 Re: Project Information

Unread post by Alez » Tue Jun 06, 2017 1:34 am

Alpha-testing is over! The project is stopped for long-term maintenance.

The work generator is stopped. BOINC server will wait for all WUs that are in-progress. The site and the forum will continue to work during the maintenance. However, the registration of new users will be suspended. The TODO list can be found here.

The alpha-testing was successful! Here are some results and conclusions.


About 5.6% (~20,500 structures) of COD entries are processed. The collected data will be used to determine the optimal set of crystallite sizes and the optimal resolution of the simulated diffraction patterns for the final database.
A few critical bugs (see e.g., 1, 2 and 3) in the app are fixed thanks to volunteers who participated in debugging on this site and on http://boinc.ru. All apps are sufficiently stable now. A fraction of fails is about 1% (see, e.g., these statistics for November 27th).
The site functionality was improved thanks to the advices given by volunteers.
The optimal parameters of the virtual server are determined: 2 cores of Intel Xeon E5-2666, 4 GB RAM, 500 GB SSD storage with read/wright throughput of 1500 IOPS, network load: 60 MB/s.
The processing power donated by volunteers to this project was much higher than expected. This allows to extend the initial range of crystallite sizes to larger sizes (up to 30 nm).
Although the MultiSize feature has slightly improved the scheduling, it is still far from optimal. It is clear now that CPU and GPU apps should receive WUs of different size due to large difference in performance. It is also clear that single-threaded CPU app is required to process small WUs. So, the distribution of WUs for different crystallite sizes between the apps should be like this:

CPU, single-threaded: < 10 nm
CPU, multi-threaded: 10 – 20 nm
GPU: > 20 nm

I will post the progress of work from time to time. However, please do not expect much until the spring of 2017.

I am very grateful to all volunteers participating in the alpha-testing! I apologize for poor server performance, awful job scheduling, app crashes and bugs leading to a waste of computational resources. Thank you for your patience and understanding!

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#3 Re: Project Information

Unread post by Alez » Tue Jun 06, 2017 1:35 am

The number of project team members has doubled!
Nikolay Khrapov agreed to join the project in 2017 as a developer of the diffraction pattern database. He will also help with the system administration. Nikolay is known to the BOINC community primarily as the system administrator for the SAT@Home project. Now things will get easier!

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#4 Re: Project Information

Unread post by Alez » Tue Jun 06, 2017 1:37 am

XaNSoNS is published in SoftwareX
The article about XaNSoNS, the software this project is based on, has been published in the peer-reviewed scientific journal SoftwareX. The article is open-access and can be found here.

The paper was submitted to the journal about a month before this project was launched, so I was able to add only a brief mention of the BOINC project during the revision process.

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