article · 2015
Shared-memory parallelism can be simple, . . .
Julian Shun
Cited by 0Abstract and details only
Abstract
Parallelism is the key to achieving high performance in computing. How-ever, writing efficient and scalable parallel programs is notoriously difficult, and often requires significant expertise. To address this challenge, it is crucial to provide programmers with high-level tools to enable them to develop solutions efficiently, and at the same time emphasize the theoretical and practical aspects of algorithm design to allow the solutions developed to run efficiently under all possible settings. This thesis addresses this challenge using a three-pronged approach consisting of the design of shared-memory programming techniques, frameworks, and algorithms for important problems in computing. The thesis provides evidence that with appropriate programming techniques, frameworks, and algorithms, shared-memory programs can be simple, fast, and scalable, both in theory and in practice. The results developed in this thesis serve to ease the transition into the multicore era. The first part of this thesis introduces tools and techniques for deterministic
Cite this paper
Shun, J. (2015). Shared-memory parallelism can be simple, . . .
Shun, Julian. “Shared-memory parallelism can be simple, . . .” 2015.
Shun, Julian. 2015. “Shared-memory parallelism can be simple, . . .”
Shun, J. (2015) ‘Shared-memory parallelism can be simple, . . ’.
@article{shun2015shared,
title = {{Shared-memory parallelism can be simple, . . .}},
author = {Shun, Julian},
year = {2015}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.