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Transactional memory (special issue introduction)

Grahn, Håkan (2010) In Journal of Parallel and Distributed Computing 70(10). p.993-1008
Abstract
Current and future processor generations are based on multicore architectures where the performance increase comes from an increasing number of cores on a chip. In order to utilize the performance potential of multicore architectures the programs also need to be parallel, but writing parallel programs is a non-trivial task. Transactional memory tries to ease parallel program development by providing atomic and isolated execution of code sequences, enabling software composability and protected access to shared data. In addition, transactional memory has the ability to execute atomic code sequences in parallel as long as no data conflicts occur. Transactional memory implementation proposals exist for both hardware and software, as well as... (More)
Current and future processor generations are based on multicore architectures where the performance increase comes from an increasing number of cores on a chip. In order to utilize the performance potential of multicore architectures the programs also need to be parallel, but writing parallel programs is a non-trivial task. Transactional memory tries to ease parallel program development by providing atomic and isolated execution of code sequences, enabling software composability and protected access to shared data. In addition, transactional memory has the ability to execute atomic code sequences in parallel as long as no data conflicts occur. Transactional memory implementation proposals exist for both hardware and software, as well as hybrid solutions. This special issue on transactional memory introduces transactional memory as a concept, presents an overview of some of the most important approaches so far, and finally, includes five articles that advances the state-of-the-art in transactional memory research. (Less)
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author
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Concurrency, Parallel programming, Multiprocessors, Transactions, Synchronization
in
Journal of Parallel and Distributed Computing
volume
70
issue
10
pages
993 - 1008
publisher
Elsevier
external identifiers
  • Scopus:77956063740
ISSN
0743-7315
DOI
10.1016/j.jpdc.2010.06.006
project
EASE
language
English
LU publication?
no
id
a8ccd80f-c347-4886-a3ca-cef266abf123 (old id 1684892)
date added to LUP
2010-09-23 13:30:16
date last changed
2016-11-16 10:25:12
@misc{a8ccd80f-c347-4886-a3ca-cef266abf123,
  abstract     = {Current and future processor generations are based on multicore architectures where the performance increase comes from an increasing number of cores on a chip. In order to utilize the performance potential of multicore architectures the programs also need to be parallel, but writing parallel programs is a non-trivial task. Transactional memory tries to ease parallel program development by providing atomic and isolated execution of code sequences, enabling software composability and protected access to shared data. In addition, transactional memory has the ability to execute atomic code sequences in parallel as long as no data conflicts occur. Transactional memory implementation proposals exist for both hardware and software, as well as hybrid solutions. This special issue on transactional memory introduces transactional memory as a concept, presents an overview of some of the most important approaches so far, and finally, includes five articles that advances the state-of-the-art in transactional memory research.},
  author       = {Grahn, Håkan},
  issn         = {0743-7315},
  keyword      = {Concurrency,Parallel programming,Multiprocessors,Transactions,Synchronization},
  language     = {eng},
  number       = {10},
  pages        = {993--1008},
  publisher    = {ARRAY(0xa14d3a0)},
  series       = {Journal of Parallel and Distributed Computing},
  title        = {Transactional memory (special issue introduction)},
  url          = {http://dx.doi.org/10.1016/j.jpdc.2010.06.006},
  volume       = {70},
  year         = {2010},
}