{"title":"Session details: Session 9B: Data Center Architectures & Power Management","authors":"Christina Delimitrou","doi":"10.1145/3262061","DOIUrl":"https://doi.org/10.1145/3262061","url":null,"abstract":"","PeriodicalId":50923,"journal":{"name":"ACM Sigplan Notices","volume":"42 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74052263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Storage consolidation in a virtualized environment introduces numerous duplications in virtual disks and imposes considerable pressure on disk I/O and caching. In this paper, we present a content l...
{"title":"Content Look-Aside Buffer for Redundancy-Free Virtual Disk I/O and Caching","authors":"Yangchun, LiuXianhua, Chengxu","doi":"10.1145/3140607.3050762","DOIUrl":"https://doi.org/10.1145/3140607.3050762","url":null,"abstract":"Storage consolidation in a virtualized environment introduces numerous duplications in virtual disks and imposes considerable pressure on disk I/O and caching. In this paper, we present a content l...","PeriodicalId":50923,"journal":{"name":"ACM Sigplan Notices","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3140607.3050762","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42361689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. EstradaZachary, SpraberyRead, YanLok, YuZhongzhi, CampbellRoy, KalbarczykZbigniew, K. IyerRavishankar
This paper extends the concepts behind cloud services to offer hypervisor-based reliability and security monitors for cloud virtual machines. Cloud VMs can be heterogeneous and as such guest OS par...
{"title":"Using OS Design Patterns to Provide Reliability and Security as-a-Service for VM-based Clouds","authors":"J. EstradaZachary, SpraberyRead, YanLok, YuZhongzhi, CampbellRoy, KalbarczykZbigniew, K. IyerRavishankar","doi":"10.1145/3140607.3050759","DOIUrl":"https://doi.org/10.1145/3140607.3050759","url":null,"abstract":"This paper extends the concepts behind cloud services to offer hypervisor-based reliability and security monitors for cloud virtual machines. Cloud VMs can be heterogeneous and as such guest OS par...","PeriodicalId":50923,"journal":{"name":"ACM Sigplan Notices","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3140607.3050759","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44471043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kai Wang, Aftab Hussain, Zhiqiang Zuo, G. Xu, Ardalan Amiri Sani
There is more than a decade-long history of using static analysis to find bugs in systems such as Linux. Most of the existing static analyses developed for these systems are simple checkers that find bugs based on pattern matching. Despite the presence of many sophisticated interprocedural analyses, few of them have been employed to improve checkers for systems code due to their complex implementations and poor scalability. In this paper, we revisit the scalability problem of interprocedural static analysis from a "Big Data" perspective. That is, we turn sophisticated code analysis into Big Data analytics and leverage novel data processing techniques to solve this traditional programming language problem. We develop Graspan, a disk-based parallel graph system that uses an edge-pair centric computation model to compute dynamic transitive closures on very large program graphs. We implement context-sensitive pointer/alias and dataflow analyses on Graspan. An evaluation of these analyses on large codebases such as Linux shows that their Graspan implementations scale to millions of lines of code and are much simpler than their original implementations. Moreover, we show that these analyses can be used to augment the existing checkers; these augmented checkers uncovered 132 new NULL pointer bugs and 1308 unnecessary NULL tests in Linux 4.4.0-rc5, PostgreSQL 8.3.9, and Apache httpd 2.2.18.
{"title":"Graspan","authors":"Kai Wang, Aftab Hussain, Zhiqiang Zuo, G. Xu, Ardalan Amiri Sani","doi":"10.1145/3093336.3037744","DOIUrl":"https://doi.org/10.1145/3093336.3037744","url":null,"abstract":"There is more than a decade-long history of using static analysis to find bugs in systems such as Linux. Most of the existing static analyses developed for these systems are simple checkers that find bugs based on pattern matching. Despite the presence of many sophisticated interprocedural analyses, few of them have been employed to improve checkers for systems code due to their complex implementations and poor scalability. In this paper, we revisit the scalability problem of interprocedural static analysis from a \"Big Data\" perspective. That is, we turn sophisticated code analysis into Big Data analytics and leverage novel data processing techniques to solve this traditional programming language problem. We develop Graspan, a disk-based parallel graph system that uses an edge-pair centric computation model to compute dynamic transitive closures on very large program graphs. We implement context-sensitive pointer/alias and dataflow analyses on Graspan. An evaluation of these analyses on large codebases such as Linux shows that their Graspan implementations scale to millions of lines of code and are much simpler than their original implementations. Moreover, we show that these analyses can be used to augment the existing checkers; these augmented checkers uncovered 132 new NULL pointer bugs and 1308 unnecessary NULL tests in Linux 4.4.0-rc5, PostgreSQL 8.3.9, and Apache httpd 2.2.18.","PeriodicalId":50923,"journal":{"name":"ACM Sigplan Notices","volume":"2 1","pages":"389 - 404"},"PeriodicalIF":0.0,"publicationDate":"2017-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81927217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Ajay, Chen Song, Aditya Singh Rathore, Chi Zhou, Wenyao Xu
As the next-generation manufacturing driven force, 3D printing technology is having a transformative effect on various industrial domains and has been widely applied in a broad spectrum of applications. It also progresses towards other versatile fields with portable battery-powered 3D printers working on a limited energy budget. While reducing manufacturing energy is an essential challenge in industrial sustainability and national economics, this growing trend motivates us to explore the energy consumption of the 3D printer for the purpose of energy efficiency. To this end, we perform an in-depth analysis of energy consumption in commercial, off-the-shelf 3D printers from an instruction-level perspective. We build an instruction-level energy model and an energy profiler to analyze the energy cost during the fabrication process. From the insights obtained by the energy profiler, we propose and implement a cross-layer energy optimization solution, called 3DGates, which spans the instruction-set, the compiler and the firmware. We evaluate 3DGates over 338 benchmarks on a 3D printer and achieve an overall energy reduction of 25%.
{"title":"3DGates","authors":"J. Ajay, Chen Song, Aditya Singh Rathore, Chi Zhou, Wenyao Xu","doi":"10.1145/3093336.3037752","DOIUrl":"https://doi.org/10.1145/3093336.3037752","url":null,"abstract":"As the next-generation manufacturing driven force, 3D printing technology is having a transformative effect on various industrial domains and has been widely applied in a broad spectrum of applications. It also progresses towards other versatile fields with portable battery-powered 3D printers working on a limited energy budget. While reducing manufacturing energy is an essential challenge in industrial sustainability and national economics, this growing trend motivates us to explore the energy consumption of the 3D printer for the purpose of energy efficiency. To this end, we perform an in-depth analysis of energy consumption in commercial, off-the-shelf 3D printers from an instruction-level perspective. We build an instruction-level energy model and an energy profiler to analyze the energy cost during the fabrication process. From the insights obtained by the energy profiler, we propose and implement a cross-layer energy optimization solution, called 3DGates, which spans the instruction-set, the compiler and the firmware. We evaluate 3DGates over 338 benchmarks on a 3D printer and achieve an overall energy reduction of 25%.","PeriodicalId":50923,"journal":{"name":"ACM Sigplan Notices","volume":"71 1","pages":"419 - 433"},"PeriodicalIF":0.0,"publicationDate":"2017-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84997686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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