Hi All,

 

We have several datasets collected using a magnified pixel size of 1.065 Ang/pixel from icosahedral virus particles that have a diameter of ~500 Ang. By down-sampling to 1.5 Ang/pixel we can use box sizes under 512 x 512 pixels and therefore run Refine3D jobs to completion on GPUs. Initial processing elsewhere has yielded reconstructions approaching 3 Ang resolution after postprocessing using the full image resolution and a 600 x 600 pixel box in Refine3D running on CPU only. My feeling is that this ought to yield better results than down-sampling. However, when we try to reproduce this on our server, jobs crash on the last iteration and sometimes cause the server to hang and require a reboot.

 

Our server specs are as follows:

2x Intel Xeon CPU Broadwell E5-2680v4 (14-core)

256GB ECC DDR4-2400 RAM

8x NVIDIA GTX 1080Ti

480GB SSD for boot

5TB SSD

8x 10TB Enterprise SAS HDD

 

I am currently trying to optimise parameters using a small subset of the dataset comprising only 1814 particles (one class from Class3D). I have tried different MPI/thread combinations, pooling different numbers of particles and copying particles either to RAM or SSD, amongst other things.

 

Incidentally, it is possible to use the full image resolution and a 512 x 512 pixel box and run on the GPU for all but the last cycle, giving 8.3 Ang resolution after the Refine3D job and 7.6 Ang resolution after postprocessing for this small dataset. However, I’m concerned that this is cropping the particles too closely and I’m losing information.

 

Any suggestions as to how I might complete these jobs with a 600 x 600 pixel box would be most welcome.

 

I attach run.out, run.err and note.txt files for a job that was the only one running on the server.

 

Many thanks in advance,

 

Dave Lawson

 

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Dr. David M. Lawson
Department of Biological Chemistry,
John Innes Centre,
Norwich,
NR4 7UH, UK.
Tel: +44-(0)1603-450725
Fax: +44-(0)1603-450018

Email: [log in to unmask]