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Symmetry 2017, 9(9), 180; doi:10.3390/sym9090180

Qinling: A Parametric Model in Speculative Multithreading

1,†
,
1,†,* and 2
1
School of Electronic and Information Engineering, Xi’an Jiaotong University, No 28, Xianning West Road, Xi’an 710049, China
2
College of Information Engineering, NorthWest Agriculture and Forestry University, No 22, Xinong Road, Yangling 712100, China
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Received: 22 July 2017 / Revised: 20 August 2017 / Accepted: 28 August 2017 / Published: 2 September 2017
(This article belongs to the Special Issue Advanced in Artificial Intelligence and Cloud Computing)
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Abstract

Speculative multithreading (SpMT) is a thread-level automatic parallelization technique that can accelerate sequential programs, especially for irregular applications that are hard to be parallelized by conventional approaches. Thread partition plays a critical role in SpMT. Conventional machine learning-based thread partition approaches applied machine learning to offline guide partition, but could not explicitly explore the law between partition and performance. In this paper, we build a parametric model (Qinling) with a multiple regression method to discover the inherent law between thread partition and performance. The paper firstly extracts unpredictable parameters that determine the performance of thread partition in SpMT; secondly, we build a parametric model Qinling with extracted parameters and speedups, and train Qinling offline, as well as apply it to predict the theoretical speedups of unseen applications. Finally, validation is done. Prophet, which consists of an automatic parallelization compiler and a multi-core simulator, is used to obtain real speedups of the input programs. Olden and SPEC2000 benchmarks are used to train and validate the parametric model. Experiments show that Qinling delivers a good performance to predict speedups of unseen programs, and provides feedback guidance for Prophet to obtain the optimal partition parameters. View Full-Text
Keywords: parametric model; speculative multithreading; Prophet parametric model; speculative multithreading; Prophet
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Li, Y.; Zhao, Y.; Liu, B. Qinling: A Parametric Model in Speculative Multithreading. Symmetry 2017, 9, 180.

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