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Optimising Dynamic Binary Modification Across ARM Microarchitectures

Gorgovan, Cosmin

[Thesis]. Manchester, UK: The University of Manchester; 2017.

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Abstract

Dynamic Binary Modification (DBM) is a technique for modifying applications at runtime, working at the level of native code. It has numerous applications, including instrumentation, translation and optimisation. However, DBM introduces a performance overhead, which in some cases can dominate execution time, making many uses impractical.While avenues for reducing this overhead have been widely explored on x86, ARM, an architecture gaining widespread adoption, has received little attention. Consequently, the overhead of DBM on ARM, as reported in the literature and measured using the available DBM systems, has fallen behind the state-of-the-art by one or two orders of magnitude. The research questions addressed in this thesis are: 1) how to develop low overhead DBM systems for the ARM architecture, and 2) whether new optimisations are plausible and needed.Towards that end, a number of novel optimisations were developed and evaluated specifically to address the sources of overhead for DBM on various ARM microarchitectures. Furthermore, many of the optimisations in the literature were ported to ARM and evaluated. This work was enabled by a new DBM system, named MAMBO, created specifically for this purpose. MAMBO, using the optimisations presented in this thesis, is able to achieve an overhead an order of magnitude smaller than that of the most efficient DBM system for ARM available at the start of this PhD.

Bibliographic metadata

Type of resource:
Content type:
Form of thesis:
Type of submission:
Degree type:
Doctor of Philosophy
Degree programme:
PhD Computer Science
Publication date:
Location:
Manchester, UK
Total pages:
151
Abstract:
Dynamic Binary Modification (DBM) is a technique for modifying applications at runtime, working at the level of native code. It has numerous applications, including instrumentation, translation and optimisation. However, DBM introduces a performance overhead, which in some cases can dominate execution time, making many uses impractical.While avenues for reducing this overhead have been widely explored on x86, ARM, an architecture gaining widespread adoption, has received little attention. Consequently, the overhead of DBM on ARM, as reported in the literature and measured using the available DBM systems, has fallen behind the state-of-the-art by one or two orders of magnitude. The research questions addressed in this thesis are: 1) how to develop low overhead DBM systems for the ARM architecture, and 2) whether new optimisations are plausible and needed.Towards that end, a number of novel optimisations were developed and evaluated specifically to address the sources of overhead for DBM on various ARM microarchitectures. Furthermore, many of the optimisations in the literature were ported to ARM and evaluated. This work was enabled by a new DBM system, named MAMBO, created specifically for this purpose. MAMBO, using the optimisations presented in this thesis, is able to achieve an overhead an order of magnitude smaller than that of the most efficient DBM system for ARM available at the start of this PhD.
Thesis main supervisor(s):
Thesis co-supervisor(s):
Language:
en

Institutional metadata

University researcher(s):

Record metadata

Manchester eScholar ID:
uk-ac-man-scw:307942
Created by:
Gorgovan, Cosmin
Created:
7th March, 2017, 15:58:54
Last modified by:
Gorgovan, Cosmin
Last modified:
3rd November, 2017, 11:18:21

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