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High Performance Computing with Data Science (MSc)

Course Description

Virtual Open Days 2017

In order to give applicants an opportunity to find out more about the MSc programmes, we offer online sessions where you can speak to teaching staff in an informal and friendly way. It's also a great opportunity to ask any questions about the MSc.

The next virtual open day is:
Wednesday 19th April, 13:00 - 14:00 BST (GMT +1)

Our Virtual Open Days are live, online events so you don't have to come to the campus. There will be two presentations followed by a Question & Answer session. No preparation is required before the sessions. The presentations will cover an introduction of the MSc programmes, course contents, career opportunities, scholarships, applying and other aspects of studying with us.

Online registration is required for the events and we will accept bookings up to three days prior to each Virtual Open Day. Please go to this link to register: http://www.epcc.ed.ac.uk/msc/applying/visiting-open-days

Programme description

You will study at EPCC, the UK’s leading supercomputing centre. EPCC is the major provider of high performance computing (HPC) training in Europe with an international reputation for excellence in HPC education and research.

Our staff have a wealth of expertise across all areas of HPC, parallel programming technologies and data science.

This MSc programme has a strong practical focus and provide access to leading- edge HPC systems such as ARCHER, which is the UK’s largest, fastest and most powerful supercomputer, with more than 100,000 CPU cores.

Data science involves the manipulation, processing and analysis of data to extract knowledge, and HPC provides the power that underpins it.

You will learn the multidisciplinary skills and knowledge in both HPC and data science to unlock the knowledge contained in the increasingly large, complex and challenging data sets that are now generated across many areas of science and business.

Programme structure

This MSc programme takes the form of two semesters of taught courses followed by a dissertation project.

Your studies will have a strong practical focus and you will have access to a wide range of HPC platforms and technologies. You will take seven compulsory courses, which provide a broad-based coverage of the fundamentals of HPC, parallel computing and data science. The option courses focus on specialist areas relevant to computational science. Assessment is by a combination of coursework and examination.

Taught courses

Compulsory courses:

Fundamentals of Data Management (Semester 1)
Message-Passing Programming (Semester 1)
Programming Skills (Semester 1)
Threaded Programming (Semester 1)
Data Analytics with High Performance Computing (Semester 2)
Software Development (Semester 2)
Project Preparation (Semester 2)

Optional courses:

HPC Architectures (Semester 1)
Parallel Numerical Algorithms (Semester 1)
Parallel Programming Languages (Semester 1)
Advanced Parallel Programming (Semester 2)
HPC Ecosystem (Semester 2)
Parallel Design Patterns (Semester 2)
Performance Programming (Semester 2)
Courses from the School of Informatics, Mathematics or Physics (up to 30 credits)

After completing the taught courses, students work on a three-month individual project leading to a dissertation. Dissertation projects may be either research-based or industry-based with an external organisation, with opportunities for placements in local companies.

Industry-based dissertation projects
Through our strong links with industry, we offer our students the opportunity to undertake their dissertation project with one of a wide range of local companies.

An industry-based dissertation project can give you the opportunity to enhance your skills and employability by tackling a real-world project, gaining workplace experience, exploring potential career paths and building relationships with local companies.

Career opportunities

Our graduates are employed across a range of commercial areas, for example software development, petroleum engineering, finance and HPC support. Others have gone on to PhD research in fields that use HPC technologies, including astrophysics, biology, chemistry, geosciences, informatics and materials science.

Visit the High Performance Computing with Data Science (MSc) page on the University of Edinburgh website for more details!

(Student Profile)

Adrian Jackson

1790.jpg I had undertaken a degree in Computer Science in Edinburgh in which my final year project was investigating Grid and parallel computing. This sparked my interest in HPC, and the MSc in HPC looked like it would satisfy this interest.

When I applied for the MSc in HPC, I really looked forward to the challenges of learning a new aspect of computing and computer science. And the ability to get hands-on with some of the world’s fastest computers. The MSc was a very intense learning experience. It was much more involved and hands-on than my degree, so the first few months were quite challenging but also very exciting. I certainly felt that after the first semester I had really experienced and learnt a wide range of new subjects and skills. The people who taught the MSc were the real strength of it, lots of experience but also approachable.

After graduating, I obtained a job at EPCC and have been here ever since. Indeed, I now teach some of the MSc course and very much enjoy supervising MSc students through their projects. My work at EPCC has been very varied, for example: working with computational scientists to improve the performance of their codes; collaborating with HPC experts from around the world on large-scale European projects, and developing solutions for companies interested in using parallel computing to solve their problems. I currently do a mixture of technical work and project management. My biggest task at the moment is managing an international collaboration that is investigating exascale computing for nuclear fusion simulations.

I'm very happy at EPCC. The varied nature of the work I get involved with is very rewarding and ensures that the job is always interesting and challenging. Hopefully in 10 years' time I will be in the position to use my experience to help manage somewhere like EPCC, so a job like director or deputy-director of an HPC centre would be ideal.

If you are thinking of coming here to do the MSc in HPC, I'd say definitely go for it. You need to have some experience of computing and writing computer programs, otherwise it's hard to get to grip with the material that is taught. But other than that, the MSc's mix of lectures and practicals enables people from lots of different academic backgrounds to get the skills and knowledge required to perform high performance computing.

(Student Profile)

Nitya Hariharan

1791.jpg I was interested in applying my Computer Science skills to Astronomy and took up the MSc in High Performance Computing because it has a wide range of applications in Computational Astrophysics. Also, Edinburgh is a well known university so I was happy to apply for a course of my choice here.

The MSc was great in terms of the course structure. It is only a year long, so it would be nice if it could be prolonged a bit more so that students can gain more experience with HPC. The best part was the amount of resources available to the students. We had access to a large number of machines with different architectures, which broadened our practical knowledge as well.

The atmosphere at EPCC is very student-friendly. I was the student representative for my group and our opinions and views were taken into account to improve future courses. We found this to be very motivating.
Edinburgh is a lovely city and I have very fond memories of it. It has everything one needs and I am sure it is a city everyone can enjoy!

I am now doing a PhD which involves both parallel computing and Astrophysics at the Max Planck Institute of Astrophysics. My current project is helping me learn how parallel computing is used by the scientific community to do better research. I have always wanted to work in this field and I found the MSc course in HPC to be a big help in getting where I am now. My MSc has given me the skills required to work with large codes on different architectures.

I would like to continue to do work similar to what I do now. That is, being able to talk to people from an IT background and with scientists. I think parallel computing is here to stay and it helps to understand this from a user's perspective and also from the perspective of an IT person who has more in-depth knowledge of supercomputers.

The MSc in HPC is a course I can highly recommend. A degree from EPCC is a good starting point for someone who wants to make a career in parallel computing.

(Student Profile)

Xu Guo

1792.jpg I chose the MSc in High performance computing (HPC) because HPC is widely used in many areas of academia and industry. It is believed to be one of the most important trends for current and future advanced technologies. I’ve been interested in HPC since I was an undergraduate, and the MSc in HPC was therefore a great opportunity for me to study this area further.

I enjoyed the one-year MSc study at EPCC very much. There was a wide range of interesting taught courses available, which we could select depending on our own interests. There were also plenty of practical sessions, which were actually the most interesting parts for me as we could use real supercomputers for our projects.

My whole year of student life in Edinburgh was great. The University of Edinburgh is one of the best universities in the UK. Being a student here means that you can enjoy the excellent quality of teaching with a wide range of resources, many supports for career development and a fantastic Scottish experience. Edinburgh is a beautiful city with many natural and historic attractions. If you want to find out about Scotland, you won’t be disappointed here!

After the MSc study, I joined EPCC as an Applications Consultant. Since then I’ve worked on many different projects. My main work focuses on applications enabling and performance analysis. I’m also teaching and supervising the MSc.

Working at EPCC means a lot of fun. I can now apply what we learnt from the MSc to real and interesting scientific research. There are many opportunities to access the most up-to-date technologies in my daily life. I really love the productive and friendly environment at EPCC and quite enjoy the work-life balance here.

In the long term, I’m still quite keen to work in the HPC field. The next 10 years should be very exciting for supercomputing. HPC plays an increasing important role in cutting-edge scientific research as well as a wide range of industrial areas.

Are you thinking of doing the MSc in HPC? Welcome and enjoy!

(Student Profile)

Omkar Kulkarni

1793.jpg When I applied to the MSc in HPC, I had worked as a software developer for 3 years. I had always been keenly interested in paral¬¬lel computing, because of the sheer complexity of the computational problems it can address. This was the perfect opportunity for me to learn under the tutelage of industry-renowned experts at EPCC, which has a long-standing association with HPC, and to gain hands-on experience of working with large parallel computers such as HECToR.

The MSc has been an immense learning experience for me. The course was perfectly paced to accommodate students from various backgrounds and ages – from fresh graduates to experienced professionals. The content was broad and touched almost every aspect of HPC. The lecturers had a thorough understanding of the subject matter and patiently helped us understand even the most difficult concepts. I also enjoyed the regular guest lectures delivered by industry experts who gave us key insights into emerging trends.

The University hosts students from almost every geographical location, cultural background and academic interest. The list of my friends in Edinburgh included writers, investment bankers, scientists, environmental engineers and economists, to name a few. I had the most memorable experiences at Edinburgh which I shall cherish forever.

I currently live in Seattle, USA, and work for Microsoft who offered me a placement while I was writing my MSc thesis. I work in the SQL Server Analysis Services team where we routinely deal with extremely large quantities of data, popularly called ‘Big Data’. The concepts learnt during the MSc are helping me understand key design decisions in the software stack and the implications of the underlying hardware, as well as to suggest improvements to extract optimal performance from our servers.

In the next 10 years, I wish to start my own venture focused on specific applications of HPC. I also hope to be able to pursue a PhD in HPC since I haven’t had enough of it just yet.

My advice to prospective students would be to think in terms of the future, as HPC will only grow and continue to infiltrate every aspect of our lives. GPUs are ubiquitous, mobile devices are already running many-core processors, and hundreds of cores on a single chip are on their way. HPC is surely the way forward, and the MSc course at the University of Edinburgh will equip you with everything you need for charting that trajectory.


Postgraduate Tuition Fee Loans (PTFL) - 20+ Awards

Loans for tuition fees and living costs are available from SAAS for eligible Scotland domiciled and EU students.Further information can be found at:

Value of Scholarship(s)

up to £3,400 for full-time students and up to £1,700 for part-time students



Application Procedure


Further Information



Masters Scholarships in High Performance Computing - 4 Awards

Up to four Masters scholarships in High Performance Computing are available for the 2016/17 academic session. Each scholarship has a value of £4,750. These awards will be tenable for one academic year and will automatically be deducted from your tuition feeThe scholarship will be awarded on the broadly basis of academic merit with candidates requiring a first-class or upper second-class (2:1) honours degree from a UK university or overseas equivalent.No separate scholarship application is required. In order to be considered for the scholarship, please apply for the MSc programmes before 1st May 2016.Successful applicants will be notified as soon as possible after the deadline.

Value of Scholarship(s)



These scholarships are open to applicants of all nationalities. All applicants who have been accepted for admission to the MSc in High Performance Computing (HPC) and the MSc in High Performance Computing with Data Science (HPC with DS) are eligible to be considered. Candidates must have, or expect to obtain, a UK first class or 2:1 Honours degree or its international equivalent.

Application Procedure

No separate scholarship application is required. In order to be considered for one of the Master’s Scholarships in High Performance Computing, please submit your application for the MSc in HPC or the MSc in HPC with Data Science by 1st May 2016.ENTRY REQUIREMENTS & HOW TO APPLY
http://www.epcc.ed.ac.uk/msc/applyingFor more information, please contact the Programme Administrator by emailing [email protected]

Further Information



Highly Skilled Workforce Scholarships - No. of awards TBC

A large number of Master's Scholarships are available for the 2016-2017 academic session at the University of Edinburgh.Scholarships are available to UK nationals who are permanently domiciled in Scotland, as well as EU nationals (excluding UK nationals) domiciled in EU or Scotland but not elsewhere in UK, who have been accepted on a eligible full-time or part-time Master's degree programme.Visit the following website for further details:

Value of Scholarship(s)

UK/EU tuition fee


Visit the following website for further details:

Application Procedure

Eligible applicants should complete an online scholarship application form at:

Further Information

http://Visit the following website for further details: http://www.ed.ac.uk/student-funding/postgraduate/uk-eu/university-scholarships/sfc-hsw

Entry Requirements

The minimum entry requirement is a relevant UK 2:1 degree, or its international equivalent, or equivalent work experience. You must also be a competent programmer, for example in C, C++, Fortran, Java or Python.

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Recipient: University of Edinburgh

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