NDLI: A Static Greedy and Dynamic Adaptive Thread Spawning Approach for Loop-Level Parallelism

Content Provider	Springer Nature Link
Author	Li, Mei Rong Zhao, Yin Liang Tao, You Wang, Qi Ming
Copyright Year	2014
Abstract	Thread-level speculation becomes more attractive for the exploitation of thread-level parallelism from irregular sequential applications. But it is common for speculative threads to fail to reach the expected parallel performance. The reason is that the performance of speculative threads is extremely complicated by the fact that it not only suffers from the imprecision of compiler-directed performance estimation due to ambiguous control and data dependences, but also depends on the underlying hardware configuration and program behaviors. Thus, this paper proposes a statically greedy and dynamically adaptive approach for loop-level speculation to dynamically determine the best loop level at runtime. It relies on the compiler to select and optimize all loop candidates greedily, which are then proceeded on the cost-benefit analysis of different loop nesting levels for the determination of the order of loop speculation. Under the runtime loop execution prediction, we dynamically schedule and update the order of loop speculation, and ensure the best loop level to be always parallelized. Two different policies are also examined to maximize overall performance. Compared with traditional static loop selection techniques, our approach can achieve comparable or better performance.
Starting Page	962
Ending Page	975
Page Count	14
File Format	PDF
ISSN	10009000
Journal	Journal of Computer Science and Technology
Volume Number	29
Issue Number	6
e-ISSN	18604749
Language	English
Publisher	Springer US
Publisher Date	2014-11-17
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	thread-level speculation loop performance prediction dynamic loop selection Computer Science Software Engineering Theory of Computation Data Structures, Cryptology and Information Theory Artificial Intelligence (incl. Robotics) Information Systems Applications (incl. Internet)
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Computational Theory and Mathematics Computer Science Applications Software Hardware and Architecture

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