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Techniques for Enhancing the Efficiency of Transactional Memory Systems
KTH, School of Electrical Engineering and Computer Science (EECS), Software and Computer systems, SCS. INESC-ID, Instituto Superior Tecnico, Universidade de Lisboa. (Distributed and Parallel Systems)
2018 (English)Doctoral thesis, monograph (Other academic)
Abstract [en]

Transactional Memory (TM) is an emerging programming paradigm that drastically simplifies the development of concurrent applications by relieving programmers from a major source of complexity: how to ensure correct, yet efficient, synchronization of concurrent accesses to shared memory. Despite the large body of research devoted to this area, existing TM systems still suffer from severe limitations that hamper both their performance and energy efficiency.

This dissertation tackles the problem of how to build efficient implementations of the TM abstraction by introducing innovative techniques that address three crucial limitations of existing TM systems by: (i) extending the effective capacity of Hardware TM (HTM) implementations; (ii) reducing the synchronization overheads in Hybrid TM (HyTM) systems; (iii) enhancing the efficiency of TM applications via energy-aware contention management schemes.

The first contribution of this dissertation, named POWER8-TM (P8TM), addresses what is arguably one of the most compelling limitations of existing HTM implementations: the inability to process transactions whose footprint exceeds the capacity of the processor's cache. By leveraging, in an innovative way, two hardware features provided by IBM POWER8 processors, namely Rollback-only Transactions and Suspend/Resume, P8TM can achieve up to 7x performance gains in workloads that stress the capacity limitations of HTM.

The second contribution is Dynamic Memory Partitioning-TM (DMP-TM), a novel Hybrid TM (HyTM) that offloads the cost of detecting conflicts between HTM and Software TM (STM) to off-the-shelf operating system memory protection mechanisms. DMP-TM's design is agnostic to the STM algorithm and has the key advantage of allowing for integrating, in an efficient way, highly scalable STM implementations that would, otherwise, demand expensive instrumentation of the HTM path. This allows DMP-TM to achieve up to 20x speedups compared to state of the art HyTM solutions in uncontended workloads.

The third contribution, Green-CM, is an energy-aware Contention Manager (CM) that has two main innovative aspects: (i) a novel asymmetric design, which combines different back-off policies in order to take advantage of Dynamic Frequency and Voltage Scaling (DVFS) hardware capabilities, available in most modern processors; (ii) an energy efficient implementation of a fundamental building block for many CM implementations, namely, the mechanism used to back-off threads for a predefined amount of time. Thanks to its innovative design, Green-CM can reduce the Energy Delay Product by up to 2.35x with respect to state of the art CMs.

All the techniques proposed in this dissertation share an important common feature that is essential to preserve the ease of use of the TM abstraction: the reliance on on-line self-tuning mechanisms that ensure robust performance even in presence of heterogeneous workloads, without requiring prior knowledge of the target workloads or architecture.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2018. , p. 143
Series
TRITA-EECS-AVL ; 2018:83
Keywords [en]
Transactional Memory, Parallel Programming, Concurrency Control, Self-tuning, Energy Efficiency, Data Partitioning, Dynamic Frequency and Voltage Scaling (DVFS), Hardware Transactional Memory (HTM)
Keywords [pt]
Memória Transacional, Programação Paralela, Eficiência Energética, Mecanismos de Auto-configuração, Partição de Dados, Frequência Dinâmica e do Escalonamento de Voltagem (DVFS), Memória Transacional em Hardware (HTM)
Keywords [sv]
Transaktionellt Minne, Parallellprogrammering, Samtida Exekvering, Självjusterande, Energieffektivitet, Datapartitionering, Dynamisk Frekvens och Volttalsskalning
National Category
Computer Systems
Research subject
Information and Communication Technology
Identifiers
URN: urn:nbn:se:kth:diva-237246ISBN: 978-91-7729-997-4 (print)OAI: oai:DiVA.org:kth-237246DiVA, id: diva2:1258335
Public defence
2018-11-23, Sal C, Electrum, Isafjordsgatan 22, Kista, 14:00 (English)
Opponent
Supervisors
Projects
Erasmus Mundus Joint Doctorate in Distributed Computing
Note

QC 20181024

Available from: 2018-10-24 Created: 2018-10-24 Last updated: 2018-10-25Bibliographically approved

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