On the design of energy‐efficient hardware transactional memory systems. (4th June 2012)

• Record Type: Journal Article
• Authors: Gaona, E.; Titos, R.; Fernández, J.; Acacio, M. E.; Schulze, Bruno; Rebello, Vinod; Moreira, Jose
• Is Part Of: Concurrency and computation. Volume 25:Number 6(2013:Apr.)
• Page Start: 862
• Page End: 880
• Publication Date: 2012-06-04
• Subjects: Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.2866
• Languages: English
• ISSNs: 1532-0626

Abstract

<abstract abstract-type="main" id="cpe2866-abs-0001"> <title>SUMMARY</title> <p id="cpe2866-para-0001">Transactional memory is currently being advocated as a promising alternative to lock‐based synchronization because it simplifies multithreaded programming. In this way, future many‐core chip multiprocessor architectures may need to provide hardware support for transactional memory. On the other hand, energy consumption constitutes nowadays a first class consideration in multicore processor designs. In this work, we characterize the performance and energy consumption of two well‐known hardware transactional memory systems that employ opposite policies for data versioning and conflict management. More specifically, we compare a LogTM‐SE <italic>eager‐eager</italic> system and a version of the Scalable Transactional Coherence and Consistency <italic>lazy‐lazy</italic> system that enable parallel commits. To do so, we extended the Multifacet GEMS simulator to estimate the energy consumed in the on‐chip caches according to CACTI and used the interconnection network energy model given by Orion 2. Results show that the energy consumption of the eager‐eager system is 38% higher in average than in the lazy‐lazy case, whereas performance differences between the two systems are 26% in average. We found that even though lazy‐lazy beats eager‐eager on average, there are considerable deviations in performance depending on the particular characteristics of each application and the settings of both systems. Finally, from this characterization, we observe that a significant part of the energy consumed in some applications in eager‐eager is spent on the back‐off delay phase and explore more energy‐efficient hardware back‐off mechanisms. For lazy‐lazy systems, the way in which memory lines are assigned to the L2 cache banks affects the number of parallel commits in some applications, and we study an alternative fine‐grained assignment. Copyright © 2012 John Wiley & Sons, Ltd.</p> </abstract>