An in-depth analysis of system-level techniques for Simultaneous Multi-threaded Processors in Clouds
To improve the overall system utilization, Simultaneous Multi-Threading (SMT) has become a norm in clouds. Usually, Hardware threads are viewed and deployed directly as physical cores for attempts to improve resource utilization and system throughput. However, context switches in virtualized systems...
| Main Authors: | , , , |
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| Format: | Monograph |
| Language: | English |
| Published: |
Unpublished
2020
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| Subjects: | |
| Online Access: | https://eprints.nottingham.ac.uk/60662/ |
| _version_ | 1848799791097577472 |
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| author | Wang, Yaohua Li, Rongze Huang, Zhentao Zhou, Xu |
| author_facet | Wang, Yaohua Li, Rongze Huang, Zhentao Zhou, Xu |
| author_sort | Wang, Yaohua |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | To improve the overall system utilization, Simultaneous Multi-Threading (SMT) has become a norm in clouds. Usually, Hardware threads are viewed and deployed directly as physical cores for attempts to improve resource utilization and system throughput. However, context switches in virtualized systems might incur severe resource waste, which further led to significant performance degradation. Worse, virtualized systems suffer from performance variations since the rescheduled vCPU may affect other hardware threads on the same physical core. In this paper, we perform an in-depth experimental study about how existing system software techniques improves the utilization of SMT Processors in Clouds. Considering the default Linux hypervisor vanilla KVM as the baseline, we evaluated two update-to-date kernel patches IdlePoll and HaltPoll through the combination of 14 real-world workloads. Our results show that mitigating they could significantly mitigate the number of context switches, which further improves the overall system throughput and decreases its latency. Based on our findings, we summarize key lessons from the previous wisdom and then discuss promising directions to be explored in the future. |
| first_indexed | 2025-11-14T20:41:16Z |
| format | Monograph |
| id | nottingham-60662 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:41:16Z |
| publishDate | 2020 |
| publisher | Unpublished |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-606622020-05-21T06:37:36Z https://eprints.nottingham.ac.uk/60662/ An in-depth analysis of system-level techniques for Simultaneous Multi-threaded Processors in Clouds Wang, Yaohua Li, Rongze Huang, Zhentao Zhou, Xu To improve the overall system utilization, Simultaneous Multi-Threading (SMT) has become a norm in clouds. Usually, Hardware threads are viewed and deployed directly as physical cores for attempts to improve resource utilization and system throughput. However, context switches in virtualized systems might incur severe resource waste, which further led to significant performance degradation. Worse, virtualized systems suffer from performance variations since the rescheduled vCPU may affect other hardware threads on the same physical core. In this paper, we perform an in-depth experimental study about how existing system software techniques improves the utilization of SMT Processors in Clouds. Considering the default Linux hypervisor vanilla KVM as the baseline, we evaluated two update-to-date kernel patches IdlePoll and HaltPoll through the combination of 14 real-world workloads. Our results show that mitigating they could significantly mitigate the number of context switches, which further improves the overall system throughput and decreases its latency. Based on our findings, we summarize key lessons from the previous wisdom and then discuss promising directions to be explored in the future. Unpublished 2020-01-01 Monograph NonPeerReviewed application/pdf en cc_by https://eprints.nottingham.ac.uk/60662/1/An%20In-depth%20Analysis%20of%20System-level%20Techniques%20for%20Simultaneous%20Multi-threaded%20Processors%20in%20Clouds.pdf Wang, Yaohua, Li, Rongze, Huang, Zhentao and Zhou, Xu (2020) An in-depth analysis of system-level techniques for Simultaneous Multi-threaded Processors in Clouds. Working Paper. Unpublished. (Unpublished) Simultaneous Multi-threading; Operating Systems; Hypervisor |
| spellingShingle | Simultaneous Multi-threading; Operating Systems; Hypervisor Wang, Yaohua Li, Rongze Huang, Zhentao Zhou, Xu An in-depth analysis of system-level techniques for Simultaneous Multi-threaded Processors in Clouds |
| title | An in-depth analysis of system-level techniques for Simultaneous Multi-threaded Processors in Clouds |
| title_full | An in-depth analysis of system-level techniques for Simultaneous Multi-threaded Processors in Clouds |
| title_fullStr | An in-depth analysis of system-level techniques for Simultaneous Multi-threaded Processors in Clouds |
| title_full_unstemmed | An in-depth analysis of system-level techniques for Simultaneous Multi-threaded Processors in Clouds |
| title_short | An in-depth analysis of system-level techniques for Simultaneous Multi-threaded Processors in Clouds |
| title_sort | in-depth analysis of system-level techniques for simultaneous multi-threaded processors in clouds |
| topic | Simultaneous Multi-threading; Operating Systems; Hypervisor |
| url | https://eprints.nottingham.ac.uk/60662/ |