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Modernise Compiler Technology with Deep Learning

PGR-P-791

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Key facts

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

Today&#039;s computing systems adsorb a huge amount of the planet&#039;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 research information section&nbsp;that the research degree you wish to be considered for is &lsquo;Modernise Compiler Technology with Deep Learning&rsquo; as well as&nbsp;<a href="https://eps.leeds.ac.uk/computing/staff/6452/dr-zheng-wang">Dr 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>&nbsp;</p>

<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><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>, <a href="https://phd.leeds.ac.uk/funding/53-school-of-computing-scholarship">School of Computing Scholarship&nbsp;</a>, <a href="https://phd.leeds.ac.uk/funding/198-akroyd-and-brown-scholarship-2022">Akroyd &amp; Brown</a>, <a href="https://phd.leeds.ac.uk/funding/199-frank-parkinson-scholarship-2022">Frank Parkinson</a> and <a href="https://phd.leeds.ac.uk/funding/204-boothman-reynolds-and-smithells-scholarship-2022">Boothman, Reynolds &amp; Smithells</a> Scholarships are available to UK applicants. &nbsp;<a href="https://phd.leeds.ac.uk/funding/60-alumni-bursary">Alumni Bursary</a> is available to graduates of the University of Leeds.&nbsp;</p> <p><strong>Non-UK</strong>&nbsp;&ndash; The&nbsp;<a href="https://phd.leeds.ac.uk/funding/53-school-of-computing-scholarship">School of Computing Scholarship&nbsp;</a>&nbsp;is available to support the additional academic fees of Non-UK applicants. 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. 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>

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

<p>For further information regarding 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>&nbsp;</p> <p>For further information regarding the project, please contact Dr 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 funding opportunities</h3>
<h3 class="heading heading--sm">Linked research areas</h3>