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Modernise Compiler Technology with Deep Learning

PGR-P-791

Key facts

Type of research degree
PhD
Application deadline
Ongoing deadline
Country eligibility
International (open to all nationalities, including the UK)
Funding
Competition funded
Supervisors
Professor Zheng Wang
Schools
School of Computing
Research groups/institutes
Distributed Systems and Services
<h2 class="heading hide-accessible">Summary</h2>

Today's computing systems adsorb a huge amount of the planet's resources. Data-centres consume 4% of global energy and are asked to perform increasingly computationally expensive tasks. Making the programs that run on them more efficient is of paramount importance. Compilers, which are solely responsible for optimising these programs, have changed little in the last several decades. Their middle ends are comprised of a large number of passes with hand-built heuristics each of which is complex and, in the aggregate, are too complex for any compiler engineer to successfully reason about.

<h2 class="heading hide-accessible">Full description</h2>

<p>Developing an optimising compiler is a highly skilled and arduous process, and there is inevitably a software delay whenever a new processor is designed. It often takes several generations of a compiler to start to effectively exploit the processors&#39; potential, by which time a new processor appears, and the process starts again. This never-ending game of catch-up means that we rarely fully exploit a shipped processor and it inevitably delays time to market.&nbsp;</p> <p>It is high time that we modernise our compiler technology. In this project, we will investigate the use of machine learning (deep learning in particular) to automate the process of designing compiler heuristics. If successful, our work will lead to compilers that can deliver good performance on any hardware architecture and can automatically catch up with the hardware evolution. Programs will be run faster and save more energy that is currently possible.</p>

<h2 class="heading">How to apply</h2>

<p>Formal applications for research degree study should be made online through the&nbsp;<a href="https://www.leeds.ac.uk/research-applying/doc/applying-research-degrees">University&#39;s website</a>. Please state clearly in the Planned Course of Study section that you are applying for <em><strong>PHD Computing FT</strong></em> and in the research information section&nbsp;that the research degree you wish to be considered for is <em><strong>Modernise Compiler Technology with Deep Learning</strong></em>&nbsp;as well as Professor&nbsp;<a href="https://eps.leeds.ac.uk/computing/staff/6452/dr-zheng-wang">Zheng Wang</a> as your proposed supervisor.</p> <p>If English is not your first language, you must provide evidence that you meet the University&#39;s minimum English language requirements (below).</p> <p style="margin-bottom:11px"><em>As an international research-intensive university, we welcome students from all walks of life and from across the world. We foster an inclusive environment where all can flourish and prosper, and we are proud of our strong commitment to student education. Across all Faculties we are dedicated to diversifying our community and we welcome the unique contributions that individuals can bring, and particularly encourage applications from, but not limited to Black, Asian, people who belong to a minority ethnic community, people who identify as LGBT+ and people with disabilities. Applicants will always be selected based on merit and ability.</em></p> <p class="MsoNoSpacing">Applications will be considered on an ongoing basis. &nbsp;Potential applicants are strongly encouraged to contact the supervisors for an informal discussion before making a formal application. &nbsp;We also advise that you apply at the earliest opportunity as the application and selection process may close early, should we receive a sufficient number of applications or that a suitable candidate is appointed.</p> <p>Please note that you must provide the following documents at the point you submit your application:</p> <ul> <li>Full Transcripts of all degree study or if in final year of study, full transcripts to date</li> <li>Personal Statement outlining your interest in the project</li> <li>CV</li> <li>Funding information including any alternative sources of funding that you are applying for or if you are able to pay your own fees and maintenance</li> </ul>

<h2 class="heading heading--sm">Entry requirements</h2>

Applicants to research degree programmes should normally have at least a first class or an upper second class British Bachelors Honours degree (or equivalent) in an appropriate discipline. The criteria for entry for some research degrees may be higher, for example, several faculties, also require a Masters degree. Applicants are advised to check with the relevant School prior to making an application. Applicants who are uncertain about the requirements for a particular research degree are advised to contact the School or Graduate School prior to making an application.

<h2 class="heading heading--sm">English language requirements</h2>

The minimum English language entry requirement for research postgraduate research study is an IELTS of 6.5 overall with at least 6.5 in writing and at 6.0 in reading, listening and speaking) or equivalent. The test must be dated within two years of the start date of the course in order to be valid. Some schools and faculties have a higher requirement.

<h2 class="heading">Funding on offer</h2>

<p style="margin-bottom:12px"><strong>Self-Funded or externally sponsored students are welcome to apply.</strong></p> <p><strong>UK</strong>&nbsp;&ndash;&nbsp;The&nbsp;<a href="https://phd.leeds.ac.uk/funding/209-leeds-doctoral-scholarships-2022">Leeds Doctoral Scholarships</a>&nbsp;and&nbsp;<a href="https://phd.leeds.ac.uk/funding/234-leeds-opportunity-research-scholarship-2022">Leeds Opportunity Research Scholarship</a> are available to UK applicants (open from October 2023). <a href="https://phd.leeds.ac.uk/funding/60-alumni-bursary">Alumni Bursary</a> is available to graduates of the University of Leeds.</p> <p><strong>Non-UK</strong> &ndash; The&nbsp;<a href="https://phd.leeds.ac.uk/funding/48-china-scholarship-council-university-of-leeds-scholarships-2021">China Scholarship Council - University of Leeds Scholarship</a>&nbsp;is available to nationals of China (open from October 2023). The&nbsp;<a href="https://phd.leeds.ac.uk/funding/73-leeds-marshall-scholarship">Leeds Marshall Scholarship</a>&nbsp;is available to support US citizens. <a href="https://phd.leeds.ac.uk/funding/60-alumni-bursary">Alumni Bursary</a> is available to graduates of the University of Leeds.</p> <p><strong>Important:&nbsp;</strong> Any costs associated with your arrival at the University of Leeds to start your PhD including flights, immigration health surcharge/medical insurance and Visa costs are not covered under this studentship.</p> <p>Please refer to the <a href="https://www.ukcisa.org.uk/">UKCISA</a> website for information regarding Fee Status for Non-UK Nationals.</p>

<h2 class="heading">Contact details</h2>

<p>For further information about your application, please contact Doctoral College Admissions:<br /> e:&nbsp;<a href="mailto:phd@engineering.leeds.ac.uk">phd@engineering.leeds.ac.uk</a>, t: +44 (0)113 343 5057.</p> <p>For further information about this project, please contact Prof. Zheng Wang by email:&nbsp;&nbsp;<a href="mailto:Z.Wang5@leeds.ac.uk">Z.Wang5@leeds.ac.uk</a></p>


<h3 class="heading heading--sm">Linked research areas</h3>