THE UNIVERSITY of EDINBURGH

DEGREE REGULATIONS & PROGRAMMES OF STUDY 2014/2015
- ARCHIVE as at 1 September 2014

University Homepage
DRPS Homepage
DRPS Search
DRPS Contact
DRPS : Course Catalogue : School of Informatics : Informatics

Postgraduate Course: Compiler Optimisation (Level 11) (INFR11032)

Course Outline
SchoolSchool of Informatics CollegeCollege of Science and Engineering
Course typeStandard AvailabilityAvailable to all students
Credit level (Normal year taken)SCQF Level 11 (Year 4 Undergraduate) Credits10
Home subject areaInformatics Other subject areaNone
Course website http://course.inf.ed.ac.uk/copt Taught in Gaelic?No
Course descriptionThis course introduces students to modern techniques in efficient implementation of programming languages. Modern processors and systems are designed based on the assumption that a compiler will be able to effectively exploit architectural resources. This course will examine in detail techniques to exploit instruction level parallelism, memory hierarchy and higher level parallelism. It will examine classic static analysis approaches to these problems and introduce newer feedback directed and dynamic approaches to optimisation. The course work will require students to implement selected optimisations in a research compiler and critically review literature in compiler optimisation.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements This course is open to all Informatics students including those on joint degrees. For external students where this course is not listed in your DPT, please seek special permission from the course organiser.

Maths background: Basic set theory, graph theory, statistics, linear algebra

Programming background: Proficient in an imperative programming language such as C. Some experience using a scripting language.
Additional Costs None
Information for Visiting Students
Pre-requisitesNone
Displayed in Visiting Students Prospectus?Yes
Course Delivery Information
Delivery period: 2014/15 Semester 2, Available to all students (SV1) Learn enabled:  No Quota:  None
Web Timetable Web Timetable
Course Start Date 12/01/2015
Breakdown of Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 20, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 76 )
Additional Notes
Breakdown of Assessment Methods (Further Info) Written Exam 75 %, Coursework 25 %, Practical Exam 0 %
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S2 (April/May)2:00
Summary of Intended Learning Outcomes
1 - Understanding of inherent computational complexity of optimisation
2 - Development of optimizations via search based approaches
3 - Ability to parallelise programs via systematic algorithms
4 - Knowledge of dynamic and adaptive approaches to modern optimisation
Assessment Information
The coursework will consist of one practical compiler exercise where students will design and implement an optimisation and evaluate it on a set of benchmarks, writing a report on their work and findings.

You should expect to spend approximately 25 hours on the coursework for this course.

If delivered in semester 1, this course will have an option for semester 1 only visiting undergraduate students, providing assessment prior to the end of the calendar year.
Special Arrangements
None
Additional Information
Academic description Not entered
Syllabus *Compiler Construction, phase order, compilation as optimisation
*Architecture costs: Parallelism and Latency in uni and multi-processors
*Architecture "independent" optimisation, dataflow analysis, lattices and fixed points
*Code generation, register allocation and scheduling in superscalar and vliw processors
*High level analysis based on dependence analysis. Intra and inter procedural analysis, whole program analysis.
*High level transformations including linear algebraic formalisation, unimodular transformations and space/time representation
*Automated parallelisation. shared and distributed memory models. Linear algebraic approach to parallelisation.
*Adaptive optimisation: Feedback directed optimisation, iterative compilation, program specialisation and dynamic compilation eg JIT, DBT
*Compiler infrastructure case studies: SUIF, Machine SUIF, JIKES
*Current themes:low power compilation, automatic compiler generation and machine learning.

Relevant QAA Computing Curriculum Sections: Compilers and Syntax Directed Tools
Transferable skills Not entered
Reading list * A. Aho,R. Sethi, J.D.Ullman Compilers: Priciples, Techniques and Tools.
* S. Muchnick, Advanced Compiler Design and Implementation Morgan Kaufmann 1997
* R. Allen K. Kennedy Optimizing Compilers for Modern Architectures: A
* K. D. Cooper, L. Torczon Engineering a Compiler Morgan Kaufmann 2003
* A selection of conference and journal paper as appropriate
Study Abroad Not entered
Study Pattern Not entered
KeywordsNot entered
Contacts
Course organiserMr Hugh Leather
Tel: (0131 6)50 2707
Email: hleather@inf.ed.ac.uk
Course secretaryMiss Claire Edminson
Tel: (0131 6)51 7607
Email: C.Edminson@ed.ac.uk
Navigation
Help & Information
Home
Introduction
Glossary
Search DPTs and Courses
Regulations
Regulations
Degree Programmes
Introduction
Browse DPTs
Courses
Introduction
Humanities and Social Science
Science and Engineering
Medicine and Veterinary Medicine
Other Information
Combined Course Timetable
Prospectuses
Important Information
 
© Copyright 2014 The University of Edinburgh - 29 August 2014 4:11 am