New "burros"
Two new high-performance machines have been recently installed, named "dejar"
and "denso". Each of them has 32 physical cores (64 logical ones with
hyperthreading), 384 GB of RAM, and about 20 TB of disk space. These new
machines will progressively replace the old burros ("dardo", "diosa", etc.)
that are very out-dated and out of warranty, and will be dedicated to
parallel programs tests, massive data reduction, intensive computing jobs,
etc. These new machines have been installed with the most recent version of
Fedora, 26, which is 5 releases newer than the Fedora version installed on the
desktop PCs (21). Due to this gap, it's possible that your programs compiled
or tested under Fedora 21 do not work straightaway under Fedora 26, and may
require some (hopefully minor) modifications or recompiling. This must be
taken into account especially if you use HTCondor (you may wish to restrict
your job to Fedora-21 machines). On the other hand, should you wish to
upgrade your desktop PC to Fedora 26 (a process which usually takes a few
hours), please let us know.
Usage policy will be the same as for the older "burros", that is, there will
be no restrictions "a priori" and every user will be able to use those
machines, just following a few basic rules:
- Before running any job on them, please check the load (use commands like
uptime or htop): if it is higher than 32, wait a bit till
it goes down before launching your application. Also check that the load does
not exceed 32 after your program starts.
- If you are testing your parallel codes, check how many cores are
being used and don't take up all the 32 cores. This machine should be used
only when developing or testing your parallel programs: if you need to run a
parallel aplication for hours or days on a large number of cores, there are
better alternatives, such as TeideHPC or LaPalma.
- These machines have a huge
disk space (about 20TB). Don't abuse it! There are no backups of your data
there, so don't use it like a storage system, and move your data to other
locations once your executions are done.
New powerful Supercomputing resources are going to be added to the IAC soon:
in due time we'll give a talk to inform you all about them.
IAC80 Virtual Observatory archive updated
As you may know, the CAMELOT/IAC80 public image archive can be accessed
through the Virtual Observatory (VO) protocols. Since 2016, we have been
adding regularly new images as soon as the one-year proprietary period ends:
recently, we have uploaded the data from May 2015 to September 2016. The
IAC80-VO archive now contains more than 160 000 images, all of them reduced
with the standard CAMELOT pipeline and appropriately astrometrized. The
easiest way to retrieve such images is using Aladin's All-VO tool, selecting
"IAC" among the available sources.
The IAC80-VO archive is maintained by the Support Astronomers Group (GAS) and
the SIE. The GAS gives us the reduced images and we adapt the metadata and
the database to comply with the VO standards using specific software
tools. If you have images, spectra and catalogues and wish to make them
world-wide available through the Virtual Observatory, do not hesitate to
contact us to help you set them up.
New IDL licenses
Starting with version 8.6, IDL has changed its licensing system, which from
now on is based on an "Activation Code" rather than on a license file. This
simplifies significantly the process of installing an IDL license, and allows
to migrate the license from an old PC to a new one in a very easy way (it can
be done by the user herself, and no longer requires the heinous "lmhostid"
string). We recommend that all users with a valid license on their laptops
upgrade IDL to v8.6.1 (the latest release) and migrate to this new license
system. Please get in touch with us for instructions: we just need to know
the "Installation number:" and "Licensed for use by:" values shown in the
"welcome message" printed on the terminal when starting IDL.
CNV and CVA
With the aim of providing better and wider support to our researchers, in
2006 we created the
SIEpedia,
where one can find detailed information about many software packages
installed at IAC, with several Tutorials, Manuals, HOWTOs, usage tips, etc.
For some time now we have seen that users from other institutions too are actively
visiting our SIEpedia. In past editions of SIEnews we mentioned that our
HOWTOs
about HTCondor are usually the most visited. This time we wish
to point out the sudden peak of visits to the HOWTOs pages for the CVN
(Curriculum Vitae Normalizado), which are referenced in several presentations and
talks about it. This peak coincides with the deadline of the last call for
projects for the "Plan Nacional I+D+i", around June/July 2017.
Cumulative visits for the first 6 days of
July 2017
We'd like to remind you that we offer support on editing and updating your
CVN or CVA, and help import your publications from ADS directly to CVN
(yes, you don't need to add by hand all your new publications in the CVN editor,
you can import them from ADS!). For further information, please visit our
CVN
SIEpedia page
Python profiling and display using RunSnakeRun
Has ever happened to you that your python application runs at a snail's pace
and takes ages to complete? Sometimes it is possible to increase the speed of
your code by doing some modifications, but it is not easy to find where you
should focus your programming efforts on (maybe there are few lines which are
called thousands of times, so a small optimization there will considerably
speed up the whole execution, or maybe you are using slow external functions
that can be replaced by faster ones, ...). To help you in this topic, there
are some tools called "profilers" which gather statistics about the execution
of your code, and show its most time-consuming parts, where the bottlenecks
are, etc. Once those areas are identified, you can optimize them and reduce
significantly the execution time. Among the several profilers and viewers for
Python, we like cProfile and the viewer
RunSnakeRun,
both already installed
on our desktop Linux PCs.
They will display a very intuitive graph showing how you application behaves
by means of a "square map" which provides a good overview of your executions.
To use them, simply run these commands:
- Get profiling data: python -m cProfile -o profiling.dat your_code.py
- Display data: /usr/pkg/python/Python-2.7.9/bin/runsnake profiling.dat
And speaking about python, let us recommend another very useful tool that
you might not know yet:
Python Glue.
This is a powerful library to explore relationships within and among related
datasets, making complex graphs in a very simple and quick way (it also allows
you to select points directly from the graphs in the same way TOPCAT does).
Mount remotely from Linux a directory in a Mac (and v.v.)
with sshfs
There exist several tools to mount directories on a remote system, the most
known of which are
NFS (the one
used to cross-mount scratch disks in our Linux network), and
Samba, which also
works on Windows and macOS PCs. A practical alternative for
Unix-based systems, which is implemented in user-land
(that is, no administrative/root access is required), is
sshfs. As the name
suggests, it mounts a remote file system via ssh.
With this, for instance, you can run Linux tools on data stored in
your Mac, or vv. run Mac applications on data in a Linux box.
Here goes a couple of pretty dumb examples (with a fictional username and machine).
- Use Acroread installed in your Mac to open a file in the Linux home
directory
mkdir -p ~/homelinux ; sshfs filemon@mortadelo:/home/filemon/ ~/homelinux
cd ~/homelinux/ ; open file.pdf
- Use the Intel compiler (only available in Linux) to compile and execute a
file in your Mac (instead of transferring files between the two platforms)
mkdir -p ~/homemac ; sshfs filemon@IPoftheMac:/Users/filemon/ ~/homemac
cd ~/homemac/ ; icc -o simul simul.c ; ./simul
- To unmount: fusermount -u ~/homelinux (same for other mountpoints)
We cannot say whether sshsf is faster or more robust (or not) than nfs or
samba, YMMV.