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Kernel-to-User-Mode Transition-Aware Hardware Scheduling.

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Title: Kernel-to-User-Mode Transition-Aware Hardware Scheduling.
Authors: Markovic, Nikola1, Nemirovsky, Daniel1, Unsal, Osman1, Valero, Mateo1, Cristal, Adrian1
Source: IEEE Micro. Jul2015, Vol. 35 Issue 4, p37-47. 11p.
Subjects: Parallelism (Linguistics), Multicore processors, Computer operating systems, Motherboards, Computer input-output equipment, Linux operating systems
Abstract: As thread-level parallelism in applications has continued to expand, so has research in chip multicore processors. More and more applications are becoming multithreaded, which should lead to a growing number of threads executing on a machine. Consequentially, the operating system will require increasingly larger amounts of CPU time to schedule these threads efficiently. Instead of perpetuating the trend of performing more-complex thread scheduling in the OS, the authors propose a scheduling mechanism that can be efficiently implemented in hardware as well. Their approach of identifying multithreaded application bottlenecks such as thread synchronization sections complements the fairness-aware scheduler method. It achieves average speedup of 11.1 and 30 percent (geometric mean) compared to the state-of-the-art Fairness-Aware Scheduler and Linux OS scheduler, respectively, while being 8 percent slower compared to the state-of-the-art bottleneck identification techniques. [ABSTRACT FROM PUBLISHER]
Copyright of IEEE Micro is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="JN" term="%22IEEE+Micro%22">IEEE Micro</searchLink>. Jul2015, Vol. 35 Issue 4, p37-47. 11p.
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  Data: <searchLink fieldCode="DE" term="%22Parallelism+%28Linguistics%29%22">Parallelism (Linguistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Multicore+processors%22">Multicore processors</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+operating+systems%22">Computer operating systems</searchLink><br /><searchLink fieldCode="DE" term="%22Motherboards%22">Motherboards</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+input-output+equipment%22">Computer input-output equipment</searchLink><br /><searchLink fieldCode="DE" term="%22Linux+operating+systems%22">Linux operating systems</searchLink>
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  Data: As thread-level parallelism in applications has continued to expand, so has research in chip multicore processors. More and more applications are becoming multithreaded, which should lead to a growing number of threads executing on a machine. Consequentially, the operating system will require increasingly larger amounts of CPU time to schedule these threads efficiently. Instead of perpetuating the trend of performing more-complex thread scheduling in the OS, the authors propose a scheduling mechanism that can be efficiently implemented in hardware as well. Their approach of identifying multithreaded application bottlenecks such as thread synchronization sections complements the fairness-aware scheduler method. It achieves average speedup of 11.1 and 30 percent (geometric mean) compared to the state-of-the-art Fairness-Aware Scheduler and Linux OS scheduler, respectively, while being 8 percent slower compared to the state-of-the-art bottleneck identification techniques. [ABSTRACT FROM PUBLISHER]
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  Data: <i>Copyright of IEEE Micro is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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