Kernel-Based Thread and Data Mapping for Improved Memory Affinity

Diener, Matthias; Cruz, Eduardo H. M.; Alves, Marco A. Z.; Navaux, Philippe O. A.; Busse, Anselm; Heiß, Hans-Ulrich

doi:10.1109/tpds.2015.2504985

Cited by 20 publications

(18 citation statements)

References 26 publications

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“…Due to resource contention and the asymmetric access time for cores to access memory on remote nodes and the local node, researchers have developed various strategies for dealing with these issues to support NUMA systems. Some focus on the memory placement and data mapping policies that try to allocate memory or migrate pages for a process on the node for improving locality or balancing of memory access. To minimize remote memory access, memory access behaviors are detected, and pages are placed on the node with the most accesses to them.…”

Section: Technology Background and Related Workmentioning

confidence: 99%

“…To reduce remote memory access and/or resource contention, existing studies use various strategies. Most of them focus on either the scheduling techniques and thread mapping strategies or memory placement and data mapping policies.…”

Section: Introductionmentioning

confidence: 99%

“…There are many related studies on the issues of thread mapping and data mapping to NUMA nodes, and their strategies substantially improve performance and energy efficiency. However, lacking the consideration of an OS kernel's internode load‐balancing activity will reduce the effect on performance improvement.…”

Section: Introductionmentioning

confidence: 99%

“…This paper develops a kernel mechanism and policies to select suitable tasks for internode load balancing, with the purpose of reducing remote memory access incurred by task migration between nodes. Our approach differs from those in other studies, which detect memory access behaviors of processes from page faults and then map thread or data to nodes to improve memory affinity. We base on the memory usage information of tasks on each node and propose the kernel‐level memory‐aware load balancing (kMLB) mechanism to improve the Linux kernel's load balancing mechanism on NUMA systems.…”

Section: Introductionmentioning

confidence: 99%

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Memory‐aware kernel mechanism and policies for improving internode load balancing on NUMA systems

Chiang

et al. 2019

Softw Pract Exp

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Although nonuniform memory access architecture provides better scalability for multicore systems, cores accessing memory on remote nodes take longer than those accessing on local nodes. Remote memory access accompanied by contention for internode interconnection degrades performance. Properly mapping threads to cores and data accessed to their nodes can substantially improve performance and energy efficiency. However, an operating system kernel's load-balancing activity may migrate threads across nodes, which thus messes up the thread mapping. Besides, subsequent data mapping behavior pays for the cost of page migration to reduce remote memory access. Once unsuitable threads are migrated, it is detrimental to system performance. This paper focuses on improving the kernel's internode load balancing on nonuniform memory access systems. We develop a memory-aware kernel mechanism and policies to reduce remote memory access incurred by internode thread migration. The Linux kernel's load balancing mechanism is modified to incorporate selection policies in the internode thread migration, and the kernel is modified to track the amount of memory used by each thread on each node. With this information, well-designed policies can then choose suitable threads for internode migration. The purpose is to avoid migrating a thread that might incur relatively more remote memory access and page migration. The experimental results show that with our mechanism and the proposed selection policies, the system performance is substantially increased when compared with the unmodified Linux kernel that does not consider memory usage and always migrates the first-fit thread in the runqueue that can be migrated to the target central processing unit.

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Section: Technology Background and Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Memory‐aware kernel mechanism and policies for improving internode load balancing on NUMA systems

Chiang

et al. 2019

Softw Pract Exp

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“…On the other hand, some of the apps which are used according to the need, when launched take some time to load into the memory and when the user is done with it, the app should either be terminated or not depending upon the memory. Now the time used by the app to load into the memory and the time when the user switches to another app which is already loaded in memory are the main issues to focus because both the times are directly depending upon the memory [6].…”

Section: Memory Managementmentioning

confidence: 99%

Resource management and security issues in mobile phone operating systems: A comparative analysis

Awan

Waqar

Faseeh

et al. 2017

Preprint

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Nowadays Mobile phones are becoming more popular in our daily lives. Mobile technology has a great effect on human life. Our daily tasks are dependent on mobile devices. Memory Management (MM), Security and Performance plays an important role in every handheld device specially in mobile phones, which are very much dependent on their operating system (OS). These embedded operating systems are on the driving seat when we talk about efficient and useful memory management and secure handling. Three popular OS in mobile phones are Android, Windows and iOS (iPhone OS). Each OS has its own way of managing the memory and provide it to certain number of applications. Android is an open software available for the people to modify as per their needs. But Windows and iOS operating systems didn"t allow their software as open source. Researchers have done a large amount of work using different mechanisms and decision makings to develop new ways to manage the memory of these OS"s. This work shows a comparative analysis of different memory management and security related techniques in above three operating systems. In this paper, we present the analysis of memory management and security in mobile phone operating systems with respect to apps, main memory, cache memory and virtual memory. Also, we compare the overall performance of these OS"s in terms of MM, security concerns. This study will help in finding better operating system in terms of efficient memory management and security.

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