Leginon

h1. Minimum Requirements and current NRAMM setup

h1. Hardware

h2. Electron Microscope/Camera with their Controling Computers (Windows)

Microscope need to have the capacity for external control and network connected (See [[Network Configuration]] section for details on that.  Here are known examples of Leginon implementation:

* FEI: [[FEI TecnaiTitan installation specifics|Tecnai, Polara, Titan Krios]] (Film recording available with  [[Windows_Camera_Package_Requirement#Film_(Only_for_FEI_Tecnai/Titan)|adaexp.exe]]

* JEOL: [[JEOL installation specifics|1230, 1400, JEM3100FSC,  3200]]

h2. Digital Camera

Gatan ([[Gatan_on_Windows-32|CCD]] and [[Gatan_K2_installation_and_setup|K2 Summit]]),  [[Tietz_camera_installation_and_setup|Tietz]], FEI ([[Eagle_camera_installation_and_setup|Eagle and Falcon]]), Direct Electron [[Adding_DE-12_to_Leginon|DE-12]]

*Note: Falcon integration does not include frame processing pipeline*

h2. A Second Computer Running Linux (CentOS at NRAMM)

At NRAMM, we separate the three activities into different computers that serve about 15 people with three microscopes that could be running at the same time.  All scopes share the same database, web server, and file server.  Each microscope has its own processing computer.

*We don't recommend using a computer with Windows PC as the second computer as an option*.

One group is able to use an unusually powerful WIndows PC (The one come with Gatan K2 Summit) as the processing server.  However, it is suspected as the reason for the acquisition of frame saving super-resolution mode to fail.

h3. CPU

Minimal 2 GHz;

* Python instance of Leginon runs only on one core on the processing server.  If you have multiple core, the rest will only be useful if you want to do other things on it.

NRAMM:

* Processing server: Single quad core (Intel Xeon E5540 2 2.53GHz).  One computer per microscope.

* Database server: Duo quad core (2.6GHz)

* Web server: Single quad core (Intel Xeon 3.00GHz)

h3. RAM

The whole system with its image processing, database query and web serving, needs significant memory.  Realistically, you will need minimal of 4GB memory for all processing+database+web server activities for one microscope operation with 4k camera that serves two persons (one operates the scope, one just look at the images from the web viewers) at the same time.  We know of at least one successful daily usage at this configuration.  For 2k camera, an all-in-one computer with 3GB memory has also been used successfully.  If you are buying a new computer, get at least 6GB memory would be a good idea. 

At NRAMM, to serve about 15 people viewing images and with three microscopes that could be running at the same time:

* Processing server: 4GB physical memory and 2 GB swap for years, and now at 6GB and 6GB, respectively.  One computer per microscope

* Database server: 16GB memory and 18GB swap.

* Web server: 4GB memory and 6GB swap.

h3. Display

Pretty much everything today would work for data acquisition. GPU server for frame alignment of DD camera is separated.  See below.

h3. File server

10 GB for the softwares and maybe a few hours worth of data collection. Much larger

for routine use. NRAMM 45Tb on raid and growing although some are archived.

h3. Network connection speed

100 Mbps might be possible; NRAMM 1 Gbps

h2. Additional need for frame-saving direct detection camera

h3. File server

Frame-saving camera such as DE-12 and K2 Summit are capable of saving movies of an exposure in addition to returning an integrated image back to Leginon.  As a result, if the function is used, the disk space required is multiple of that of the image.  Leginon saves the frames as non-gain corrected 16-bit integer, rather than dark/gain-corrected 32-float mrc.  Therefore, the additional storage requirement is approximately *number_of_frames/2* times larger.  Typical number_of_frames used in DE is 10-50 frames and in K2 Summit 20-30 frames.  These frames should be off-loaded from the camera computer or saved to network drive as soon as possible so not to over-load the camera computer.

In addition, to use the information in the frame movies, these raw frames must be [[appion:GainDark_correction_of_the_raw_frame_with_or_without_drift_correction|gain/dark corrected]] and saved as 32-bit float mrc stack.  For K2 Summit Counted/Super-resolution mode, the alignment of the frame is also esssential.  This means that at some point, the data related to one image will be

<pre>

number_of_frames * (0.5 + 1 + 1)

</pre>

times more than non-frame saving ones.  Factoring in that hundreds of such image may be acquired within a 24 hr session, it is therefore important to take this into account in allocating the data storage system for long term.

NRAMM's current setup:

# 10 Gbs network between frame saving camera and the file server.

# Raw frames are transferred off camera with rsync using [[DDD raw frame file transfer|rawtransfer.py]] which also removed the finished frame stack on the camera to make room for more to come.

# These raw frames are needed if default frame processing does not give optimal results.  We keep these on network drive for 30 days and make it user's responsibility to archive this on external drives. bzip or bzip2 are commonly used by the users to compress the files.  Since the raw frames are integers, it can be easily compressed to 4-10 times smaller.

# In the [[appion:GainDark_correction_of_the_raw_frame_with_or_without_drift_correction|frame processing]] Appion script, if frame alignment is performed (usually finished within a day or two after data acquisition), the un-aligned frame stack is removed since majority of the problem require re-correction.

# The frame-aligned stack is integrated and saved in the Leginon database as "-a" images. 95% of the users do not require frame-aligned stack after this point.

h3. DD Frame-alignment server

A good gpu is needed for frame alignment using the program described in Li et. al. (2013) Nat. Method vol. 10 pp584-590.

If real-time speed is desired, parallel processing on multiple hosts may be needed.

minimum: A CUDA 5.0 capable standard linux computer that you don't need to access its monitor (and hence using gpu for display) during the alignment computation.  We have used

GeForce GTX 470, Tesla C1060 and GeForce GTX 690 with success.  Large memory is very desirable for the purpose.

NRAMM's current best setup (This is on a shared resource so we don't get use this much all the time):

* up to 4 node gpu cluster each with 128 GB RAM and Intel(R) Xeon(R) CPU E5-2650 0 @ 2.00GHz & NvidiaTesla M2090 GPU.  (These have 16 cpu but only one is used per job)

h1. Software

h2. Leginon system components developed at Leginon home

Leginon Home:  "http://www.leginon.org/":http://www.leginon.org/

h2. Supporting packages and programs available through internet or your Linux distribution

There are minimum of ten packages or single programs, some of them are included in your

Linux distribution.

h2. Leginon supporting programs available upon request

*adaexp.exe* that is required if film exposure is to be made through Leginon on FEI Tecnai

machines is available by request. Please contact Max Otten: (mto at nl.feico.com)

and let him know what version of the Tecnai user interface you are using.

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[[Graphical User Interface|< Graphical User Interface]] | [[Getting Started|Getting Started >]]

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