In this tutorial we'll be showing you how to visualise HEALPix results using
Jupyter Notebook in our OnDemand appliance
on the Apocrita HPC cluster. We'll start with installing the required Python
packages before demonstrating how to run the
Information about running other components of HEALPix not covered in
this tutorial can be found on our
Hello! I am Sherman and I have just joined the
RSE team at
Queen Mary. Glad to meet you all!
My background is in computational statistics and machine learning. I have
completed projects in rainfall prediction, defect detection for 3D printing and
Markov chains using Monte Carlo. These projects involved collaboration with
various scientists, such as meteorologists, engineers and statisticians.
Over the past year, researchers from QMUL's William
Harvey Research Institute (WHRI) have engaged on a collaborative code review
club. Through this collaborative effort the group aims to peer review the
computational components of their research and provide code quality
assurance to all involved researchers. Additionally, the Research
Software Engineering group of ITS Research has been assisting the group with
knowledge transfer and by participating in the review process.
Research Software London is a community to support
the use and development of research software in London and the South East.
Since 2019, RSLondon has run a number of
Software Carpentry workshops to
teach introductory computing skills to researchers. ITSR have been involved
in these efforts, providing instructors and helpers at each of these workshops.
When it comes to picking a distribution, Python programmers are spoilt for
choice. We're going to compare two of the most popular (CPython and Anaconda)
and one that promises big performance improvements with relatively little
hassle (Intel Distribution for Python).
In this tutorial we'll be showing you how to run a
TensorFlow job using the
GPU nodes on the Apocrita HPC
cluster. We will expand upon the essentials provided on the QMUL HPC
docs site, and provide more explanation of the process.
We'll start with software installation before demonstrating a simple task and
a more complex real-world example that you can adapt for your own jobs, along
with tips on how to check if the GPU is being used.
Jigsaw puzzles proved wildly popular during lockdown, but they weren't all
done on the dining room table on rainy afternoons. The puzzle faced by
researchers from the School of English and Drama (SED), lead by
Dr Richard Coulton and in
collaboration with the Natural History Museum, was
to piece together a set of beautiful botanical watercolours brought back from
China by the East India Company surgeon James Cuninghame. Cuninghame
purchased these works, by an unknown local artist, in Xiamen in 1699. Sometime
in the first half of the eighteenth century, perhaps because of their large
size, these watercolours were cut up and glued into what you ungenerously,
call a scrap book. The British Library has lovingly digitised this book in a
high resolution images funded by Oak Spring Garden Foundation, who also
sponsored the current project.
On Apocrita we can use OpenMP to execute code on GPU devices. This post looks
at how to compile such programs and submit them to run on the GPU nodes. The
post assumes that you have code, already developed and tested, which is ready
for deployment, and that you have been granted access to the GPU nodes.