Low Overhead Dynamic Binary Translation on ARM
- Submitting institution
-
The University of Manchester
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 75547085
- Type
- E - Conference contribution
- DOI
-
10.1145/3062341.3062371
- Title of conference / published proceedings
- Proceedings of the 38th ACM SIGPLAN Conference on Programming Language Design and Implementation, PLDI 2017
- First page
- 333
- Volume
- -
- Issue
- -
- ISSN
- -
- Open access status
- -
- Month of publication
- June
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
-
A - Computer Science
- Citation count
- 7
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- "This paper was the first to propose a Dynamic Binary Translation solution for ARM architectures without significant performance degradation, allowing removal of legacy hardware (32 bit) from modern processors (64 bit), whilst maintaining software compatibility.
Distinguished Paper Award PLDI2017 (acceptance: 47/322, 15%). Only 5 UK university-led papers received this award since 2014.
Result was a key enabler in persuading ARM Ltd to award `Centre of Excellence’ status (including GBP50,000 annual donation) to Manchester.
Enabled a GBP5,800,000 (Innovate UK) project, led by THG, part of Digital Security by Design Industrial Challenge.
Invited talks: Arm Ltd, Qualcomm, Marvell, Huawei and Canonical."
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
