Improving performance and security of indirect memory references on speculative execution machines

Indirect memory references hobble efficient and secure execution on current processor architectures. Traditional hardware techniques such as caches and speculative execution are ineffective on demanding workloads, such as in-memory databases, machine learning, and graph analytics. While terabytes of DRAM are now available in public cloud machines, indirect memory references in large working sets often incur the full penalty of a random DRAM access. Furthermore, caches and speculative execution enable the recently discovered Spectre family of side-channel attacks, which allow untrusted neighbors in a public cloud to steal secrets. In this thesis, we introduce complementary software and hardware techniques to improve the performance of caches and speculative execution, and to block the largest attack class with low overhead. MILK is our C++ extension to improve data cache locality.

Name thesis:degree_name

Doctoral

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2019

Author dc:creator

• Kiriansky, Vladimir L.(Vladimir Lubenov),1979-

Advisor dc:contributor.advisor

• Saman Amarasinghe.

• Electrical Engineering and Computer Science.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/122556

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/122556