Speculative instructions execution requires dynamic branch predictors to increase the performance of a processor by executing from predicted branch target routines. Conventional Scalar architectures such as the Superscalar or Multiscalar architecture executes from a single stream, while a Multithreaded architecture executes from multiple streams at a time. Several aggressive branch predictors have been proposed with high prediction accuracies. Unfortunately, none of the branch predictors can provide 100% accuracy. Therefore, there is an inherent limitation on speculative execution in real implementation. In this paper, we show that Multithreaded architecture is a better candidate for utilizing speculative execution than Scalar architectures. Generally the branch prediction performance degradation is compounded for larger window sizes on Scalar architectures, while for a Multithreaded architecture, by increasing the number of executing threads, we could sustain a higher performance for a large aggregated speculative window size. Hence, heavier workloads may increase performance and utilization for Multithreaded architectures. We present analytical and simulation results to support our argument.
End of preview. The entire article is 9 pages. To view the full-text, please rent this article to continue.
/lp/association-for-computing-machinery/a-comparison-of-the-effect-of-branch-prediction-on-multithreaded-and-Y5KdaYRT04
Welcome to DeepDyve! Rent Premier Research Articles and Save Up to 90%
A comparison of the effect of branch prediction on multithreaded and scalar architectures
Golla, Prasad N.; Lin, Eric C.
Follow ACM SIGARCH Computer Architecture News
, Volume 26 (4)
Association for Computing Machinery – Sep 1, 1998
More Info
More Like This Article
View All dataSource[]=actageo&dataSource[]=aspet&dataSource[]=aaos&dataSource[]=aacc&dataSource[]=aacr&dataSource[]=aea&dataSource[]=aip&dataSource[]=ajnr&dataSource[]=ams&dataSource[]=aps_physical&dataSource[]=appi_book&dataSource[]=appi_journal&dataSource[]=apha&dataSource[]=asip&dataSource[]=asm&dataSource[]=asn&dataSource[]=aspb&dataSource[]=avs&dataSource[]=annual_reviews&dataSource[]=arxiv&dataSource[]=acm&dataSource[]=berghahn&dataSource[]=cabi&dataSource[]=clinical_trials&dataSource[]=dailymed&dataSource[]=degruyter&dataSource[]=du_press&dataSource[]=esa&dataSource[]=eu_press&dataSource[]=elsevier&dataSource[]=emerald&dataSource[]=ejtr&dataSource[]=emea&dataSource[]=epo&dataSource[]=faseb&dataSource[]=gsa&dataSource[]=health_affairs&dataSource[]=hindawi&dataSource[]=imanager&dataSource[]=imedpub&dataSource[]=informa_healthcare&dataSource[]=informs&dataSource[]=iop&dataSource[]=iucr&dataSource[]=iospress&dataSource[]=jbjs&dataSource[]=leftcoast&dataSource[]=lu_press&dataSource[]=mesharpe&dataSource[]=mary_ann_liebert&dataSource[]=medline&dataSource[]=mit_press&dataSource[]=nature&dataSource[]=oxford&dataSource[]=pier_professional&dataSource[]=pnas&dataSource[]=portlandpress&dataSource[]=psyc_articles&dataSource[]=psyc_books&dataSource[]=psyc_critiques&dataSource[]=plos_journal&dataSource[]=pubmed_central&dataSource[]=rsna&dataSource[]=rockefeller&dataSource[]=rcn&dataSource[]=ria&dataSource[]=rsc&dataSource[]=sage&dataSource[]=spie&dataSource[]=springer_journal&dataSource[]=springer&dataSource[]=taylor_francis&dataSource[]=aps&dataSource[]=the_scientist&dataSource[]=uc_press&dataSource[]=uspto_abstract&dataSource[]=wiley&dataSource[]=pct
© 2012 DeepDyve, Inc. All rights reserved.
Terms of Service | Privacy Policy
