Petter Svärd, B. Hudzia, Johan Tordsson, E. Elmroth
Despite the widespread support for live migration of Virtual Machines (VMs) in current hypervisors, these have significant shortcomings when it comes to migration of certain types of VMs. More specifically, with existing algorithms, there is a high risk of service interruption when migrating VMs with high workloads and/or over low-bandwidth networks. In these cases, VM memory pages are dirtied faster than they can be transferred over the network, which leads to extended migration downtime. In this contribution, we study the application of delta compression during the transfer of memory pages in order to increase migration throughput and thus reduce downtime. The delta compression live migration algorithm is implemented as a modification to the KVM hypervisor. Its performance is evaluated by migrating VMs running different type of workloads and the evaluation demonstrates a significant decrease in migration downtime in all test cases. In a benchmark scenario the downtime is reduced by a factor of 100. In another scenario a streaming video server is live migrated with no perceivable downtime to the clients while the picture is frozen for eight seconds using standard approaches. Finally, in an enterprise application scenario, the delta compression algorithm successfully live migrates a very large system that fails after migration using the standard algorithm. Finally, we discuss some general effects of delta compression on live migration and analyze when it is beneficial to use this technique.
{"title":"Evaluation of delta compression techniques for efficient live migration of large virtual machines","authors":"Petter Svärd, B. Hudzia, Johan Tordsson, E. Elmroth","doi":"10.1145/1952682.1952698","DOIUrl":"https://doi.org/10.1145/1952682.1952698","url":null,"abstract":"Despite the widespread support for live migration of Virtual Machines (VMs) in current hypervisors, these have significant shortcomings when it comes to migration of certain types of VMs. More specifically, with existing algorithms, there is a high risk of service interruption when migrating VMs with high workloads and/or over low-bandwidth networks. In these cases, VM memory pages are dirtied faster than they can be transferred over the network, which leads to extended migration downtime. In this contribution, we study the application of delta compression during the transfer of memory pages in order to increase migration throughput and thus reduce downtime. The delta compression live migration algorithm is implemented as a modification to the KVM hypervisor. Its performance is evaluated by migrating VMs running different type of workloads and the evaluation demonstrates a significant decrease in migration downtime in all test cases. In a benchmark scenario the downtime is reduced by a factor of 100. In another scenario a streaming video server is live migrated with no perceivable downtime to the clients while the picture is frozen for eight seconds using standard approaches. Finally, in an enterprise application scenario, the delta compression algorithm successfully live migrates a very large system that fails after migration using the standard algorithm. Finally, we discuss some general effects of delta compression on live migration and analyze when it is beneficial to use this technique.","PeriodicalId":202844,"journal":{"name":"International Conference on Virtual Execution Environments","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115911611","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}
This paper presents an approach to the safe execution of applications based on software-based fault isolation and policy-based system call authorization. A running application is encapsulated in an additional layer of protection using dynamic binary translation in user-space. This virtualization layer dynamically recompiles the machine code and adds multiple dynamic security guards that verify the running code to protect and contain the application. The binary translation system redirects all system calls to a policy-based system call authorization framework. This interposition framework validates every system call based on the given arguments and the location of the system call. Depending on the user-loadable policy and an extensible handler mechanism the framework decides whether a system call is allowed, rejected, or redirect to a specific user-space handler in the virtualization layer. This paper offers an in-depth analysis of the different security guarantees and a performance analysis of libdetox, a prototype of the full protection platform. The combination of software-based fault isolation and policy-based system call authorization imposes only low overhead and is therefore an attractive option to encapsulate and sandbox applications to improve host security.
{"title":"Fine-grained user-space security through virtualization","authors":"Mathias Payer, T. Gross","doi":"10.1145/1952682.1952703","DOIUrl":"https://doi.org/10.1145/1952682.1952703","url":null,"abstract":"This paper presents an approach to the safe execution of applications based on software-based fault isolation and policy-based system call authorization. A running application is encapsulated in an additional layer of protection using dynamic binary translation in user-space. This virtualization layer dynamically recompiles the machine code and adds multiple dynamic security guards that verify the running code to protect and contain the application.\u0000 The binary translation system redirects all system calls to a policy-based system call authorization framework. This interposition framework validates every system call based on the given arguments and the location of the system call. Depending on the user-loadable policy and an extensible handler mechanism the framework decides whether a system call is allowed, rejected, or redirect to a specific user-space handler in the virtualization layer.\u0000 This paper offers an in-depth analysis of the different security guarantees and a performance analysis of libdetox, a prototype of the full protection platform. The combination of software-based fault isolation and policy-based system call authorization imposes only low overhead and is therefore an attractive option to encapsulate and sandbox applications to improve host security.","PeriodicalId":202844,"journal":{"name":"International Conference on Virtual Execution Environments","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125289974","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}
Qin Zhao, David Koh, Syed Raza, Derek Bruening, W. Wong, Saman P. Amarasinghe
In today's multi-core systems, cache contention due to true and false sharing can cause unexpected and significant performance degradation. A detailed understanding of a given multi-threaded application's behavior is required to precisely identify such performance bottlenecks. Traditionally, however, such diagnostic information can only be obtained after lengthy simulation of the memory hierarchy. In this paper, we present a novel approach that efficiently analyzes interactions between threads to determine thread correlation and detect true and false sharing. It is based on the following key insight: although the slowdown caused by cache contention depends on factors including the thread-to-core binding and parameters of the memory hierarchy, the amount of data sharing is primarily a function of the cache line size and application behavior. Using memory shadowing and dynamic instrumentation, we implemented a tool that obtains detailed sharing information between threads without simulating the full complexity of the memory hierarchy. The runtime overhead of our approach --- a 5x slowdown on average relative to native execution --- is significantly less than that of detailed cache simulation. The information collected allows programmers to identify the degree of cache contention in an application, the correlation among its threads, and the sources of significant false sharing. Using our approach, we were able to improve the performance of some applications up to a factor of 12x. For other contention-intensive applications, we were able to shed light on the obstacles that prevent their performance from scaling to many cores.
{"title":"Dynamic cache contention detection in multi-threaded applications","authors":"Qin Zhao, David Koh, Syed Raza, Derek Bruening, W. Wong, Saman P. Amarasinghe","doi":"10.1145/1952682.1952688","DOIUrl":"https://doi.org/10.1145/1952682.1952688","url":null,"abstract":"In today's multi-core systems, cache contention due to true and false sharing can cause unexpected and significant performance degradation. A detailed understanding of a given multi-threaded application's behavior is required to precisely identify such performance bottlenecks. Traditionally, however, such diagnostic information can only be obtained after lengthy simulation of the memory hierarchy.\u0000 In this paper, we present a novel approach that efficiently analyzes interactions between threads to determine thread correlation and detect true and false sharing. It is based on the following key insight: although the slowdown caused by cache contention depends on factors including the thread-to-core binding and parameters of the memory hierarchy, the amount of data sharing is primarily a function of the cache line size and application behavior. Using memory shadowing and dynamic instrumentation, we implemented a tool that obtains detailed sharing information between threads without simulating the full complexity of the memory hierarchy. The runtime overhead of our approach --- a 5x slowdown on average relative to native execution --- is significantly less than that of detailed cache simulation. The information collected allows programmers to identify the degree of cache contention in an application, the correlation among its threads, and the sources of significant false sharing. Using our approach, we were able to improve the performance of some applications up to a factor of 12x. For other contention-intensive applications, we were able to shed light on the obstacles that prevent their performance from scaling to many cores.","PeriodicalId":202844,"journal":{"name":"International Conference on Virtual Execution Environments","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116353687","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}
Server virtualization technology facilitates the creation of an elastic computing infrastructure on demand. There are cloud applications like server-based computing and virtual desktop that concern startup latency and require impromptu requests for VM creation in a real-time manner. Conventional template-based VM creation is a time consuming process and lacks flexibility for the deployment of stateful VMs. In this paper, we present an abstraction of VM substrate to represent generic VM instances in miniature. Unlike templates that are stored as an image file in disk, VM substrates are docked in memory in a designated VM pool. They can be activated into stateful VMs without machine booting and application initialization. The abstraction leverages an arrange of techniques, including VM miniaturization, generalization, clone and migration, storage copy-on-write, and on-the-fly resource configuration, for rapid deployment of VMs and VM clusters on demand. We implement a prototype on a Xen platform and show that a server with typical configuration of TB disk and GB memory can accommodate more substrates in memory than templates in disk and stateful VMs can be created from the same or different substrates and deployed on to the same or different physical hosts in a cluster without causing any configuration conflicts. Experimental results show that general purpose VMs or a VM cluster for parallel computing can be deployed in a few seconds. We demonstrate the usage of VM substrates in a mobile gaming application.
{"title":"Rethink the virtual machine template","authors":"Kun Wang, J. Rao, Chengzhong Xu","doi":"10.1145/1952682.1952690","DOIUrl":"https://doi.org/10.1145/1952682.1952690","url":null,"abstract":"Server virtualization technology facilitates the creation of an elastic computing infrastructure on demand. There are cloud applications like server-based computing and virtual desktop that concern startup latency and require impromptu requests for VM creation in a real-time manner. Conventional template-based VM creation is a time consuming process and lacks flexibility for the deployment of stateful VMs. In this paper, we present an abstraction of VM substrate to represent generic VM instances in miniature. Unlike templates that are stored as an image file in disk, VM substrates are docked in memory in a designated VM pool. They can be activated into stateful VMs without machine booting and application initialization. The abstraction leverages an arrange of techniques, including VM miniaturization, generalization, clone and migration, storage copy-on-write, and on-the-fly resource configuration, for rapid deployment of VMs and VM clusters on demand. We implement a prototype on a Xen platform and show that a server with typical configuration of TB disk and GB memory can accommodate more substrates in memory than templates in disk and stateful VMs can be created from the same or different substrates and deployed on to the same or different physical hosts in a cluster without causing any configuration conflicts. Experimental results show that general purpose VMs or a VM cluster for parallel computing can be deployed in a few seconds. We demonstrate the usage of VM substrates in a mobile gaming application.","PeriodicalId":202844,"journal":{"name":"International Conference on Virtual Execution Environments","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131799675","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}
Dan Williams, H. Jamjoom, Yew-Huey Liu, Hakim Weatherspoon
With the intense competition between cloud providers, oversubscription is increasingly important to maintain profitability. Oversubscribing physical resources is not without consequences: it increases the likelihood of overload. Memory overload is particularly damaging. Contrary to traditional views, we analyze current data center logs and realistic Web workloads to show that overload is largely transient: up to 88.1% of overloads last for less than 2 minutes. Regarding overload as a continuum that includes both transient and sustained overloads of various durations points us to consider mitigation approaches also as a continuum, complete with tradeoffs with respect to application performance and data center overhead. In particular, heavyweight techniques, like VM migration, are better suited to sustained overloads, whereas lightweight approaches, like network memory, are better suited to transient overloads. We present Overdriver, a system that adaptively takes advantage of these tradeoffs, mitigating all overloads within 8% of well-provisioned performance. Furthermore, under reasonable oversubscription ratios, where transient overload constitutes the vast majority of overloads, Overdriver requires 15% of the excess space and generates a factor of four less network traffic than a migration-only approach.
{"title":"Overdriver: handling memory overload in an oversubscribed cloud","authors":"Dan Williams, H. Jamjoom, Yew-Huey Liu, Hakim Weatherspoon","doi":"10.1145/1952682.1952709","DOIUrl":"https://doi.org/10.1145/1952682.1952709","url":null,"abstract":"With the intense competition between cloud providers, oversubscription is increasingly important to maintain profitability. Oversubscribing physical resources is not without consequences: it increases the likelihood of overload. Memory overload is particularly damaging. Contrary to traditional views, we analyze current data center logs and realistic Web workloads to show that overload is largely transient: up to 88.1% of overloads last for less than 2 minutes. Regarding overload as a continuum that includes both transient and sustained overloads of various durations points us to consider mitigation approaches also as a continuum, complete with tradeoffs with respect to application performance and data center overhead. In particular, heavyweight techniques, like VM migration, are better suited to sustained overloads, whereas lightweight approaches, like network memory, are better suited to transient overloads. We present Overdriver, a system that adaptively takes advantage of these tradeoffs, mitigating all overloads within 8% of well-provisioned performance. Furthermore, under reasonable oversubscription ratios, where transient overload constitutes the vast majority of overloads, Overdriver requires 15% of the excess space and generates a factor of four less network traffic than a migration-only approach.","PeriodicalId":202844,"journal":{"name":"International Conference on Virtual Execution Environments","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127744688","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}
Dynamic binary translators(DBTs) provide powerful platforms for building dynamic program monitoring and adaptation tools. DBTs, however, have high memory demands because they cache translated code and auxiliary code to a software code cache and must also maintain data structures to support the code cache. The high memory demands make it difficult for memory-constrained embedded systems to take advantage of DBT-based tools. Previous research on DBT memory management focused on the translated code and auxiliary code only. However, we found that data structures are comparable to the code cache in size. We show that the translated code size, auxiliary code size and the data structure size interact in a complex manner, depending on the path selection (trace selection and link formation) strategy. Therefore, holistic memory efficiency (comprising translated code, auxiliary code and data structures) cannot be improved by focusing on the code cache only. In this paper, we use path selection for improving holistic memory efficiency which in turn impacts performance in memory-constrained environments. Although there has been previous research on path selection, such research only considered performance in memory-unconstrained environments. The challenge for holistic memory efficiency is that the path selection strategy results in complex interactions between the memory demand components. Also, individual aspects of path selection and the holistic memory efficiency may impact performance in complex ways. We explore these interactions to motivate path selection targeting holistic memory demand. We enumerate all the aspects involved in a path selection design and evaluate a comprehensive set of approaches for each aspect. Finally, we propose a path selection strategy that reduces memory demands by 20% and at the same time improves performance by 5-20% compared to an industrial-strength DBT.
{"title":"DBT path selection for holistic memory efficiency and performance","authors":"Apala Guha, K. Hazelwood, M. Soffa","doi":"10.1145/1735997.1736018","DOIUrl":"https://doi.org/10.1145/1735997.1736018","url":null,"abstract":"Dynamic binary translators(DBTs) provide powerful platforms for building dynamic program monitoring and adaptation tools. DBTs, however, have high memory demands because they cache translated code and auxiliary code to a software code cache and must also maintain data structures to support the code cache. The high memory demands make it difficult for memory-constrained embedded systems to take advantage of DBT-based tools. Previous research on DBT memory management focused on the translated code and auxiliary code only. However, we found that data structures are comparable to the code cache in size. We show that the translated code size, auxiliary code size and the data structure size interact in a complex manner, depending on the path selection (trace selection and link formation) strategy. Therefore, holistic memory efficiency (comprising translated code, auxiliary code and data structures) cannot be improved by focusing on the code cache only. In this paper, we use path selection for improving holistic memory efficiency which in turn impacts performance in memory-constrained environments. Although there has been previous research on path selection, such research only considered performance in memory-unconstrained environments.\u0000 The challenge for holistic memory efficiency is that the path selection strategy results in complex interactions between the memory demand components. Also, individual aspects of path selection and the holistic memory efficiency may impact performance in complex ways. We explore these interactions to motivate path selection targeting holistic memory demand. We enumerate all the aspects involved in a path selection design and evaluate a comprehensive set of approaches for each aspect. Finally, we propose a path selection strategy that reduces memory demands by 20% and at the same time improves performance by 5-20% compared to an industrial-strength DBT.","PeriodicalId":202844,"journal":{"name":"International Conference on Virtual Execution Environments","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129739450","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}
Asymmetric multicore processors (AMP) consist of cores exposing the same instruction-set architecture (ISA) but varying in size, frequency, power consumption and performance. AMPs were shown to be more power efficient than conventional symmetric multicore processors, and it is therefore likely that future multicore systems will include cores of different types. AMPs derive their efficiency from core specialization: instruction streams can be assigned to run on the cores best suited to their demands for architectural resources. System efficiency is improved as a result. To perform effective matching of threads to cores, the thread scheduler must be asymmetry-aware; and while asymmetry-aware schedulers for operating systems are a well studied topic, asymmetry-awareness in hypervisors has not been addressed. A hypervisor must be asymmetry-aware to enable proper functioning of asymmetry-aware guest operating systems; otherwise they will be ineffective in virtual environments. Furthermore, a hypervisor must ensure that asymmetric cores are shared among multiple guests in a fair fashion or in accordance with their priorities. This work for the first time implements simple changes to the hypervisor scheduler, required to make it asymmetry-aware, and evaluates the benefits and overheads of these asymmetry-aware mechanisms. Our evaluation was performed using an open source hypervisor Xen on a real multicore system where asymmetry was emulated via CPU frequency scaling. We compared the asymmetry-aware hypervisor to default Xen. Our results indicate that asymmetry support can be implemented with low overheads, and resulting performance improvements can be significant, reaching up to 36% in our experiments. Most performance improvements are derived from the fact that an asymmetry-aware hypervisor ensures that the fast cores do not go idle before slow cores and from the fact that it maps virtual cores to physical cores for asymmetry-aware guests according to the guest's expectations. Other benefits from asymmetry awareness are fairer sharing of computing resources among VMs and more stable execution times.
{"title":"AASH: an asymmetry-aware scheduler for hypervisors","authors":"Vahid Kazempour, Ali Kamali, Alexandra Fedorova","doi":"10.1145/1735997.1736011","DOIUrl":"https://doi.org/10.1145/1735997.1736011","url":null,"abstract":"Asymmetric multicore processors (AMP) consist of cores exposing the same instruction-set architecture (ISA) but varying in size, frequency, power consumption and performance. AMPs were shown to be more power efficient than conventional symmetric multicore processors, and it is therefore likely that future multicore systems will include cores of different types. AMPs derive their efficiency from core specialization: instruction streams can be assigned to run on the cores best suited to their demands for architectural resources. System efficiency is improved as a result. To perform effective matching of threads to cores, the thread scheduler must be asymmetry-aware; and while asymmetry-aware schedulers for operating systems are a well studied topic, asymmetry-awareness in hypervisors has not been addressed. A hypervisor must be asymmetry-aware to enable proper functioning of asymmetry-aware guest operating systems; otherwise they will be ineffective in virtual environments. Furthermore, a hypervisor must ensure that asymmetric cores are shared among multiple guests in a fair fashion or in accordance with their priorities.\u0000 This work for the first time implements simple changes to the hypervisor scheduler, required to make it asymmetry-aware, and evaluates the benefits and overheads of these asymmetry-aware mechanisms. Our evaluation was performed using an open source hypervisor Xen on a real multicore system where asymmetry was emulated via CPU frequency scaling. We compared the asymmetry-aware hypervisor to default Xen. Our results indicate that asymmetry support can be implemented with low overheads, and resulting performance improvements can be significant, reaching up to 36% in our experiments. Most performance improvements are derived from the fact that an asymmetry-aware hypervisor ensures that the fast cores do not go idle before slow cores and from the fact that it maps virtual cores to physical cores for asymmetry-aware guests according to the guest's expectations. Other benefits from asymmetry awareness are fairer sharing of computing resources among VMs and more stable execution times.","PeriodicalId":202844,"journal":{"name":"International Conference on Virtual Execution Environments","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129317088","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}
Application profiling is a popular technique to improve program performance based on its behavior. Offline profiling, although beneficial for several applications, fails in cases where prior program runs may not be feasible, or if changes in input cause the profile to not match the behavior of the actual program run. Managed languages, like Java and C#, provide a unique opportunity to overcome the drawbacks of offline profiling by generating the profile information online during the current program run. Indeed, online profiling is extensively used in current VMs, especially during selective compilation to improve program startup performance, as well as during other feedback-directed optimizations. In this paper we illustrate the drawbacks of the current reactive mechanism of online profiling during selective compilation. Current VM profiling mechanisms are slow -- thereby delaying associated transformations, and estimate future behavior based on the program's immediate past -- leading to potential misspeculation that limit the benefits of compilation. We show that these drawbacks produce an average performance loss of over 14.5% on our set of benchmark programs, over an ideal offline approach that accurately compiles the hot methods early. We then propose and evaluate the potential of a novel strategy to achieve similar performance benefits with an online profiling approach. Our new online profiling strategy uses early determination of loop iteration bounds to predict future method hotness. We explore and present promising results on the potential, feasibility, and other issues involved for the successful implementation of this approach.
{"title":"Novel online profiling for virtual machines","authors":"Manjiri A. Namjoshi, P. Kulkarni","doi":"10.1145/1735997.1736016","DOIUrl":"https://doi.org/10.1145/1735997.1736016","url":null,"abstract":"Application profiling is a popular technique to improve program performance based on its behavior. Offline profiling, although beneficial for several applications, fails in cases where prior program runs may not be feasible, or if changes in input cause the profile to not match the behavior of the actual program run. Managed languages, like Java and C#, provide a unique opportunity to overcome the drawbacks of offline profiling by generating the profile information online during the current program run. Indeed, online profiling is extensively used in current VMs, especially during selective compilation to improve program startup performance, as well as during other feedback-directed optimizations.\u0000 In this paper we illustrate the drawbacks of the current reactive mechanism of online profiling during selective compilation. Current VM profiling mechanisms are slow -- thereby delaying associated transformations, and estimate future behavior based on the program's immediate past -- leading to potential misspeculation that limit the benefits of compilation. We show that these drawbacks produce an average performance loss of over 14.5% on our set of benchmark programs, over an ideal offline approach that accurately compiles the hot methods early. We then propose and evaluate the potential of a novel strategy to achieve similar performance benefits with an online profiling approach. Our new online profiling strategy uses early determination of loop iteration bounds to predict future method hotness. We explore and present promising results on the potential, feasibility, and other issues involved for the successful implementation of this approach.","PeriodicalId":202844,"journal":{"name":"International Conference on Virtual Execution Environments","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128835637","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}
Min Lee, A. Krishnakumar, P. Krishnan, Navjot Singh, S. Yajnik
Virtualization technology enables server consolidation and has given an impetus to low-cost green data centers. However, current hypervisors do not provide adequate support for real-time applications, and this has limited the adoption of virtualization in some domains. Soft real-time applications, such as media-based ones, are impeded by components of virtualization including low-performance virtualization I/O, increased scheduling latency, and shared-cache contention. The virtual machine scheduler is central to all these issues. The goal in this paper is to adapt the virtual machine scheduler to be more soft-real-time friendly. We improve two aspects of the VMM scheduler -- managing scheduling latency as a first-class resource and managing shared caches. We use enterprise IP telephony as an illustrative soft real-time workload and design a scheduler S that incorporates the knowledge of soft real-time applications in all aspects of the scheduler to support responsiveness. For this we first define a laxity value that can be interpreted as the target scheduling latency that the workload desires. The load balancer is also designed to minimize the latency for real-time tasks. For cache management, we take cache-affinity into account for real time tasks and load-balance accordingly to prevent cache thrashing. We measured cache misses and demonstrated that cache management is essential for soft real time tasks. Although our scheduler S employs a different design philosophy, interestingly enough it can be implemented with simple modifications to the Xen hypervisor's credit scheduler. Our experiments demonstrate that the Xen scheduler with our modifications can support soft real-time guests well, without penalizing non-real-time domains.
{"title":"Supporting soft real-time tasks in the xen hypervisor","authors":"Min Lee, A. Krishnakumar, P. Krishnan, Navjot Singh, S. Yajnik","doi":"10.1145/1735997.1736012","DOIUrl":"https://doi.org/10.1145/1735997.1736012","url":null,"abstract":"Virtualization technology enables server consolidation and has given an impetus to low-cost green data centers. However, current hypervisors do not provide adequate support for real-time applications, and this has limited the adoption of virtualization in some domains. Soft real-time applications, such as media-based ones, are impeded by components of virtualization including low-performance virtualization I/O, increased scheduling latency, and shared-cache contention. The virtual machine scheduler is central to all these issues. The goal in this paper is to adapt the virtual machine scheduler to be more soft-real-time friendly.\u0000 We improve two aspects of the VMM scheduler -- managing scheduling latency as a first-class resource and managing shared caches. We use enterprise IP telephony as an illustrative soft real-time workload and design a scheduler S that incorporates the knowledge of soft real-time applications in all aspects of the scheduler to support responsiveness. For this we first define a laxity value that can be interpreted as the target scheduling latency that the workload desires. The load balancer is also designed to minimize the latency for real-time tasks. For cache management, we take cache-affinity into account for real time tasks and load-balance accordingly to prevent cache thrashing. We measured cache misses and demonstrated that cache management is essential for soft real time tasks. Although our scheduler S employs a different design philosophy, interestingly enough it can be implemented with simple modifications to the Xen hypervisor's credit scheduler. Our experiments demonstrate that the Xen scheduler with our modifications can support soft real-time guests well, without penalizing non-real-time domains.","PeriodicalId":202844,"journal":{"name":"International Conference on Virtual Execution Environments","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130475249","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}
Crash dump, or core dump is the typical way to save memory image on system crash for future offline debugging and analysis. However, for typical server machines with likely abundant memory, the time of core dump can significantly increase the mean time to repair (MTTR) by delaying the reboot-based recovery, while not dumping the failure context for analysis would risk recurring crashes on the same problems. In this paper, we propose several optimization techniques for core dump in virtualized environments, in order to shorten the MTTR of consolidated virtual machines during crashes. First, we parallelize the process of crash dump and the process of rebooting the crashed VM, by dynamically reclaiming and allocating memory between the crashed VM and the newly spawned VM. Second, we use the virtual machine management layer to introspect the critical data structures of the crashed VM to filter out the dump of unused memory. Finally, we implement disk I/O rate control between core dump and the newly spawned VM according to user-tuned rate control policy to balance the time of crash dump and quality of services in the recovery VM. We have implemented a working prototype, Vicover, that optimizes core dump on system crash of a virtual machine in Xen, to minimize the MTTR of core dump and recovery as a whole. In our experiment on a virtualized TPC-W server, Vicover shortens the downtime caused by crash dump by around 5X.
{"title":"Optimizing crash dump in virtualized environments","authors":"Yijian Huang, Haibo Chen, B. Zang","doi":"10.1145/1735997.1736003","DOIUrl":"https://doi.org/10.1145/1735997.1736003","url":null,"abstract":"Crash dump, or core dump is the typical way to save memory image on system crash for future offline debugging and analysis. However, for typical server machines with likely abundant memory, the time of core dump can significantly increase the mean time to repair (MTTR) by delaying the reboot-based recovery, while not dumping the failure context for analysis would risk recurring crashes on the same problems.\u0000 In this paper, we propose several optimization techniques for core dump in virtualized environments, in order to shorten the MTTR of consolidated virtual machines during crashes. First, we parallelize the process of crash dump and the process of rebooting the crashed VM, by dynamically reclaiming and allocating memory between the crashed VM and the newly spawned VM. Second, we use the virtual machine management layer to introspect the critical data structures of the crashed VM to filter out the dump of unused memory. Finally, we implement disk I/O rate control between core dump and the newly spawned VM according to user-tuned rate control policy to balance the time of crash dump and quality of services in the recovery VM.\u0000 We have implemented a working prototype, Vicover, that optimizes core dump on system crash of a virtual machine in Xen, to minimize the MTTR of core dump and recovery as a whole. In our experiment on a virtualized TPC-W server, Vicover shortens the downtime caused by crash dump by around 5X.","PeriodicalId":202844,"journal":{"name":"International Conference on Virtual Execution Environments","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125793364","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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