Data Centric and Adaptive Source Changing Transactional Memory with Exit Functionality

  • Herath Mudiyanselage Isuru Herath

Student thesis: Phd

Abstract

Multi-core computing is becoming ubiquitous due to the scaling limitations of single-core computing. It is inevitable that parallel programming will become the mainstream for such processors. In this paradigm shift, the concept of abstraction should not be compromised. A programming model serves as an abstraction of how programs are executed. Transactional Memory (TM) is a technique proposed to maintain lock free synchronization. Due to the simplicity of the abstraction provided by it, TM can also be used as a way of distributing parallel work, maintaining coherence and consistency. Motivated by this, at a higher level, the thesis makes three contributions and all are centred around Hardware Transactional Memory (HTM).As the first contribution, a transaction-only architecture is coupled with a ``data centric" approach, to address the scalability issues of the former whilst maintaining its simplicity. This is achieved by grouping together memory locations having similar access patterns and maintaining coherence and consistency according to the group each memory location belongs to. As the second contribution a novel technique is proposed to reduce the number of false transaction aborts which occur in a signature based HTM. The idea is to adaptively switch between cache lines and signatures to detect conflicts. That is, when a transaction fits in the L1 cache, cache line information is used to detect conflicts and signatures are used otherwise. As the third contribution, the thesis makes a case for having an exit functionality in an HTM. The objective of the proposed functionality, TM_EXIT, is to terminate a transaction without restarting or committing.
Date of Award1 Aug 2014
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorMikel Lujan Moreno (Supervisor)

Keywords

  • Parallel Computer Architecture
  • Hardware Transactional Memory

Cite this

'