The public defense of Jakob Danielsson’s licentiate thesis in Computer Science
The public defense of Jakob Danielsson’s licentiate thesis in Computer science will take place at Mälardalen University, room Paros (Västerås Campus) at 13:15 on December 17, 2019.
Title: “Characterisation of Shared Resource Contention in Multi-core Systems”.
Serial number: 287.
The faculty examiner is Associate Professor Stefano Di Carlo Politecnico di Torino and the examining committee consists of Associate Professor Lei Feng, KTH and Professor Jan Carlsson, Mälardalen University.
Reserve; Assistant Professor Joaquín Ballesteros Gómez, University of Malaga.
Multi-core computers are infamous for being hard to use in time-critical systems due to execution-time variations. In this thesis we study the problem of shared resource contention which occurs when multiple applications executing on different cores and do not have exclusive ownership of a shared resource. We investigate performance variations of parallel tasks in multi-core systems and pinpoint the source of the performance variation and resource contention using performance counters.
Furthermore, we investigate methods to mitigate performance variations using resource isolation techniques. We present a methodology for verifying isolation and tested the achieved isolation using the Jailhouse hypervisor. We further investigate shared cache memory isolation opportunities using a page coloring tool called PALLOC. Page-coloring is used for partitioning the cache, assigning specific cache lines to specific processes. Page coloring can however cause system performance degradation since it decreases the total amount of cache memory available for each process.
Therefore, finally, we propose a dynamic partitioning assignment policy which assigns cache partitions to a process according to an adaptive model based on the process performance. The general conclusion from our investigations is that a large body of applications can suffer from shared resource contention and that techniques for mitigating resource contention. Our methods measure characterize applications, identifies resource contention and finally suggests on isolation techniques.