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Extreme Computing

Extreme Computing is about making the most of a computing cluster, be it processing huge data sets or serving high-volume websites. The course covers high-performance computing at several levels of the stack:
Big data problems, the memory hierarchy, latency requirements, performance considerations, and economics
Processing large amounts of data, sharding, streaming, query processing, and randomised algorithms
Distributed file systems, fault tolerance, replication, job scheduling, and MapReduce/Hadoop
We aim to make students aware of topics using large (> 1000 node) clusters, but not be tied to particular vendors whereever possible. If you want to understand how companies like Amazon, Facebook, Google, Microsoft, and Twitter work, then this is the course for you.


Lectures are Mondays and Thursdays 17:10-18:00 in George Square Lecture Theatre. Labs start week 3.

Who to Contact

Almost Everything. Including all questions about the labs or assignments outside lab sessions.
Informatics Teaching Organisation
Assignment extensions and lab time changes
Computing Support
Lab and cluster logins (DICE account)
Harsh marking
The Original Marker
Clear marker error (i.e. failed to add marks correctly, missed a solution). Marks can go up or down.
Marker error appeals. Include e-mail from the original marker. Marks can go up or down.
Lecturer: Kenneth Heafield
Office: 4.21, Informatics Forum, 10 Crichton Street
E-mail: exc at (but please use Piazza)


Students should be familiar with the Unix command line and ssh. Information systems provides a primer on the command line.

We do not require a particular programming language. Examples are mostly in Python and Java with occasional C++.

The is a Level-11 course, normally taken in Year 4. It is open to all 4th year, MInf, and MSc students in Informatics.

Mailing List

Announcements regarding the course will be posted to the course mailing list. All students taking the course are automatically subscribed to this list. Previous postings can be accessed using the mailing list archive.

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