Three Years of Service

On June 28th 2016, after a lot of hard work by a lot of people to bring High Performance Computing to the University of Hull, Viper ran its first production job.

A Tweet celebrating Viper's first job

Now three years later, Viper has made a massive contribution to research here at the university. Over 1.5 million jobs have been run, consuming around 70 million CPU hours (that is work that would take around 8,000 years on a single processor). Viper is certainly kept busy, with resource utilisation often over 90% full and the scheduler busy ensuring fair access for our users.

Viper has transformed research, helping people scale simulations and models beyond what they had been able to previously contemplate, enabling new avenues of research and new approaches to research, and helped reduce time to publication.

A big thanks to you all at the viper team, work that was taking me a month to complete now takes a matter of hours!

A P.S. on a recent email!

Over 200 research staff and students have run jobs on Viper as part of their work and while the more traditional High Performance Computing research areas (Astrophysics, Computational Chemistry, Computer Science, Engineering, Bioinformatics, Environmental Sciences etc) are among the more common jobs seen running on Viper, over the last three years Viper has contributed to research across the University with increasing use from the Faculties of Arts, Cultures and Education,  Health Sciences and Business, Law and Politics. It is fantastic to see the diversity of people making use of Viper and the sort of research being carried out.

In October 2016 we saw the first publication to come from work carried out on Viper, and there are now 40 publications (that we know of) on our publications list at

A Tweet celebrating Viper's first publication

As well as publications we have seen work carried out on Viper presented at numerous conferences and contributed to many PhD and Masters theses and undergraduate student projects. Viper has been represented at Science Festivals and other outreach events with the HPC administration team and users helping the public to understand what HPC is and what the impact has been on research at the university and beyond.

We would like to thank everyone for their hard work in these three years: all those involved in getting Viper to the University of Hull in the first place; everyone who has been involved in the HPC Steering Group; our colleagues past and present involved in supporting Viper, and not least all of our users!

In terms of the future Viper still has a lot to offer the research community here at the University of Hull. The HPC administration team are working hard behind the scenes on an update to the Viper software stack that should bring some exciting new functionality and performance improvements to Viper.

There is lots more research to be done and lots more jobs to run!

Keras – simplifying deep learning

With the HPC Viper team, the senior RSE has been investigating the python API Keras which vastly simplifies the programming of deep learning computational graphs. Using a number of the free-available data sets including the mnist character sets. The outcomes have been very encouraging and allow the researcher to concentrate on the neural nets interconnections rather than the depth of programming and optimisation that other libraries demand.

A typical neural net can be constructed with 9 lines of code, as below:

model = Sequential()

model.add(Convolution2D(32, 3, 3, activation='relu', input_shape=(1,28,28)))
model.add(Convolution2D(32, 3, 3, activation='relu'))

model.add(Dense(128, activation='relu'))
model.add(Dense(10, activation='softmax'))

GTC Europe 2017

Nvidia’s GTC-Europe conference was held at Munich, Germany this year. It not only showcases the latest development in hardware development but is strongly based on the technologies of machine learning and now deep learning. The conference as always starts with a 2/3 hour keynote speech by Nvidia’s founder and CEO Jensen Huang; areas covered were:

  • Where GPU fit in and the re-engagement of Moore’s law
  • Growth of deep learning applications (Nobel prizes in physics and chemistry)
  • Use of image classification and other GPU industries
  • Nvidia’s holodeck technology
  • Intelligent machines (referencing IoT)
  • Autonomous Driverless cars
  • Pegasus (Robo taxi drive PX)
  • Project Isaac (AI robot simulator)


Matlab on Viper

Matlab is a widely used tool in research, thanks in part to the ability to quickly develop code to test solutions without (necessarily) needing to be a expert coder, and a wealth of toolboxes and functions from image and signal processing, to bioinformatics, econometrics and robotics. However, Matlab can be quite resource hungry and if you find your PC struggling or yourself waiting for Matlab to finish processing before doing other things on your computer, or even if you just want to get your Matlab tasks running more quickly and efficiently, then you might want to think about using Matlab on Viper. Why? Continue reading “Matlab on Viper”

Projects, Placements and Fun

Ceph Project

Work has continued on my Intern project, with the virtual cluster completed, I tested various different backup solutions to use with Ceph e.g. BackupPC and BorgBackup. I have also looked into benchmarking the Ceph cluster once installed using tools such as rados bench and fio. The Hard drives for the compute nodes have arrived for the cluster so the next stage will be installing the new hard drives into Viper’s compute nodes ready for the installation of Ceph. Continue reading “Projects, Placements and Fun”

A Year of Service

I’m sitting in a hotel lobby in Amsterdam catching up on work emails and putting the finishing touches to our latest newsletter which will be out shortly. The newsletter celebrates a year of research on Viper, having gone live on the 28th June 2016. It has been a fantastic journey over the last year, meeting new users, hearing of the impact Viper can have on someones research and seeing research outputs published.

Continue reading “A Year of Service”

Write maintainable research code with these 3 weird tricks!

Writing code is not easy.

If you are a researcher and have to write code, especially if you are not from a computer science background, then I salute you.

I have spent the last 4 years (6 years if you include my time at the Open University) studying for an MEng in Software Engineering. I can tell you with certainty that it is not an easy task. I’d like to tell you about something that is even harder than writing code: Reading and maintaining poorly written code! Continue reading “Write maintainable research code with these 3 weird tricks!”