Improving Web Server Performance Through Main Memory Compression

Beltrán, Vicenç; Torres, Jordi; Ayguadé, Eduard

doi:10.1109/icpads.2008.15

Cited by 17 publications

(5 citation statements)

References 11 publications

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“…To reduce swap delay time in a web server, V. Beltran et al [10] used compression and in-memory swaps. When an application requests a page that is not in memory, the kernel seeks the requested page in the compressed swap area.…”

Section: Related Workmentioning

confidence: 99%

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Compressed and shared swap to extend available memory in virtualized consumer electronics

Lee

Hong

Yoo

2014

IEEE Trans. Consumer Electron.

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Virtualization has recently been applied to consumer electronic (CE) devices such as smart TVs and smartphones. In these virtualized CE devices, memory is a valuable resource, because the virtual machines (VMs) on the devices must share the same physical memory. However, physical memory is usually partitioned and allocated to each VM. This partitioning technique may result in memory shortages, which can seriously degrade application performance. This paper proposes a new swap mechanism for virtualized CE devices with flash memory. This proposed mechanism reduces memory consumption by compressing and sharing unused pages. This swap mechanism stores the unused page in memory of another VM, to increase the available memory of the original VM. The proposed swap mechanism is implemented on the Xen hypervisor and Linux. The mechanism improves the application performance by up to 38% by significantly reducing the number of swap-out requests. The swap-out requests are reduced by up to 88% compared to previous swap mechanisms. Moreover, the mechanism reduces memory consumption of the swap area by up to 79%. 1

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Section: Related Workmentioning

confidence: 99%

“…In the past, in-memory swap mechanisms using compression have been proposed to reduce swap delay time [9], [10], or to provide a swap mechanism for systems without a disk [4], [5]. These mechanisms compress swapped-out pages and store them in a swap area in the main memory instead of disk storage.…”

Section: Related Workmentioning

confidence: 99%

Compressed and shared swap to extend available memory in virtualized consumer electronics

Lee

Hong

Yoo

2014

IEEE Trans. Consumer Electron.

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“…Therefore, it has been used in one way or another by most commercial OSs for personal computers [24], [25]. A few compressed swap schemes for server systems have also been proposed to meet the strong memory demand of highly consolidated VMs or memory-intensive workloads [26]- [28].…”

Section: Background and Related Work A Memory Overcommitment Tecmentioning

confidence: 99%

$ezswap$ : Enhanced Compressed Swap Scheme for Mobile Devices

Kim

Seo

2019

IEEE Access

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The limited memory capacity of mobile devices leads to the popular use of compressed swap schemes, which reduce the I/O operations involving the swapping in and out of infrequently accessed pages. However, most of the current compressed swap schemes indiscriminately compress and store all swap-out pages. Considering that both energy and computing power are scarce resources in mobile devices, and modern applications frequently deal with already-compressed multimedia data, this blind approach may cause adverse impacts. In addition, they focus only on anonymous pages and not on file-mapped pages, because the latter are backed by on-disk files. However, our observations revealed that, in mobile devices, file-mapped pages consume significantly more memory than anonymous pages. Last but not least, most of the current compressed swap schemes blindly follow the least-recently-used (LRU) discipline when choosing the victim pages for replacement, not considering the compression ratio or data density of the cached pages. To overcome the aforementioned problems and maximize the memory efficiency, we propose a compressed swap scheme, called enhanced zswap (ezswap), for mobile devices. ezswap accommodates not only anonymous pages, but also clean file-mapped pages. It estimates the compression ratio of incoming pages with their information entropy, and selectively compresses and caches the pages only with beneficial compression ratios. In addition, its admission control and cache replacement algorithms are based on a costbenefit model that considers not only the access recency of cached pages but also their information density and expected eviction cost. The proposed scheme was implemented in the Linux kernel for Android. Our evaluation with a series of commercial applications demonstrated that it reduced the amount of flash memory read by up to 55%, thereby improving the application launch time by up to 22% in comparison to the original zswap.

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“…Data distribution and work balance are explicitly considered within the language definition. The use of accelerators to improve general system performance has been studied in [9], but this work is focused on a single node, while our work is aimed to exploit this accelerators in a distributed environment.…”

Section: Related Workmentioning

confidence: 99%

Speeding Up Distributed MapReduce Applications Using Hardware Accelerators

Becerra

Beltrán

Carrera

et al. 2009

2009 International Conference on Parallel Processing

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Abstract-In an attempt to increase the performance/cost ratio, large compute clusters are becoming heterogeneous at multiple levels: from asymmetric processors, to different system architectures, operating systems and networks. Exploiting the intrinsic multi-level parallelism present in such a complex execution environment has become a challenging task using traditional parallel and distributed programming models. As a result, an increasing need for novel approaches to exploiting parallelism has arisen in these environments. MapReduce is a data-driven programming model originally proposed by Google back in 2004 as a flexible alternative to the existing models, specially devoted to hiding the complexity of both developing and running massively distributed applications in large compute clusters. In some recent works, the MapReduce model has been also used to exploit parallelism in other non-distributed environments, such as multi-cores, heterogeneous processors and GPUs. In this paper we introduce a novel approach for exploiting the heterogeneity of a Cell BE cluster linking an existing MapReduce runtime implementation for distributed clusters and one runtime to exploit the parallelism of the Cell BE nodes. The novel contribution of this work is the design and evaluation of a MapReduce execution environment that effectively exploits the parallelism existing at both the Cell BE cluster level and the heterogeneous processors level.

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Improving Web Server Performance Through Main Memory Compression

Abstract: Abstract

Cited by 17 publications

References 11 publications

Compressed and shared swap to extend available memory in virtualized consumer electronics

Compressed and shared swap to extend available memory in virtualized consumer electronics

$ezswap$ : Enhanced Compressed Swap Scheme for Mobile Devices

Speeding Up Distributed MapReduce Applications Using Hardware Accelerators

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