I/O Deduplication

Koller, Ricardo; Rangaswami, Raju

doi:10.1145/1837915.1837921

Cited by 173 publications

(12 citation statements)

References 19 publications

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“…We select three data sets to test our model, which are MSR, 35 VDI‐LUN, 36 and KC. MSR data set contains 1‐week block I/O traces of enterprise servers on 13 servers at Microsoft Research Cambridge.…”

Section: Methodsmentioning

confidence: 99%

A data grouping model based on cache transaction for unstructured data storage systems

Zhu

Sun

et al. 2021

Int J of Intelligent Sys

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Cache prefetching technology has become the mainstream data access optimization strategy in the Industrial Intelligent Systems (IIS) and the data centers. However, the rapidly increasing of unstructured data generates massive pairwise access relationships. Therefore, researchers have to make a choice between spatial locality and temporal locality to ensure an acceptable computational complexity. We propose cache-transaction-based data grouping model (CTDGM) to solve the problems described above by optimizing the feature representation method and grouping efficiency. First, we provide the definition of the cache transaction and propose the method for extracting the cache transaction feature (CTF). Second, we design a data chunking algorithm based on CTF and spatiotemporal locality to optimize the relationship calculation efficiency.Third, we propose CTDGM by constructing a relation graph that groups data into independent groups according to the strength of the data access relation. Based on the results of the experiment, compared with the state-of-the-art and traditional methods, our algorithm achieves an average increase in the cache hit rate of 5%-20% on the MSR, VDI-LUN, and KC

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Section: Methodsmentioning

confidence: 99%

A data grouping model based on cache transaction for unstructured data storage systems

Zhu

Sun

et al. 2021

Int J of Intelligent Sys

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“…MSNfs is the I/O trace gathered in the MSN Storage back-end file server [Kavalanekar et al 2008]. The Homes workload is collected from the home directory in an NFS server, which consists of several research group activities such as developing, testing, technical writing, and plotting [Koller and Rangaswami 2010]. The remaining three workloads, FileZilla, Torrent, and GIMP, are from in-house traces [ESOSLab 2012].…”

Section: Case Studiesmentioning

confidence: 99%

“…They propose that there should be an interface to inform the SSD of its Power Budget and that the firmware of an SSD should be designed to dynamically adjust the parallelism degree subject to its Power Budget. Several works have proposed dynamically throttling the transfer rate or parallelism degree of an SSD to regulate the temperature of the SSD [Park et al 2009b;Lee et al 2013]. To properly design the SSD internal parallelism, we need to incorporate the channel switch delay, way switch delay, and page write latency.…”

Section: Peak Energy Consumptionmentioning

confidence: 99%

“…Energy density of an SSD, that is, J/in 3 , is orders of magnitude larger than that of an HDD, and the peak energy consumption of an SSD is much higher than that of an HDD [Inoue et al 2011], which raises the heat dissipation issue. A number of works are dedicated to regulating the peak energy consumption via throttling the data transfer rate or limiting the number of flash memory chips programmed in parallel [Park et al 2009b;Lee et al 2013]. Compared to HDDs, SSDs will make CPU spend less time waiting for an I/O.…”

Section: Related Workmentioning

confidence: 99%

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Design Tradeoffs of SSDs

et al. 2015

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In this work, we studied the energy consumption characteristics of various SSD design parameters. We developed an accurate energy consumption model for SSDs that computes aggregate, as well as componentspecific, energy consumption of SSDs in sub-msec time scale. In our study, we used five different FTLs (page mapping, DFTL, block mapping, and two different hybrid mappings) and four different channel configurations (two, four, eight, and 16 channels) under seven different workloads (from large-scale enterprise systems to small-scale desktop applications) in a combinatorial manner. For each combination of the aforementioned parameters, we examined the energy consumption for individual hardware components of an SSD (microcontroller, DRAM, NAND flash, and host interface). The following are some of our findings. First, DFTL is the most energy-efficient address-mapping scheme among the five FTLs we tested due to its good write amplification and small DRAM footprint. Second, a significant fraction of energy is being consumed by idle flash chips waiting for the completion of NAND operations in the other channels. FTL should be designed to fully exploit the internal parallelism so that energy consumption by idle chips is minimized. Third, as a means to increase the internal parallelism, increasing way parallelism (the number of flash chips in a channel) is more effective than increasing channel parallelism in terms of peak energy consumption, performance, and hardware complexity. Fourth, in designing high-performance and energy-efficient SSDs, channel switching delay, way switching delay, and page write latency need to be incorporated in an integrated manner to determine the optimal configuration of internal parallelism.

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“…We implement Ditto and evaluate its performance with both synthesized and real-world workloads [37,67,83]. Ditto is more elastic than Redis regarding resource efficiency and the speed of resource adjustments.…”

Section: Introductionmentioning

confidence: 99%

Ditto: An Elastic and Adaptive Memory-Disaggregated Caching System

Shen,

Zuo,

Luo

et al. 2023

Proceedings of the 29th Symposium on Operating Systems Principles

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In-memory caching systems are fundamental building blocks in cloud services. However, due to the coupled CPU and memory on monolithic servers, existing caching systems cannot elastically adjust resources in a resource-efficient and agile manner. To achieve better elasticity, we propose to port inmemory caching systems to the disaggregated memory (DM) architecture, where compute and memory resources are decoupled and can be allocated flexibly. However, constructing an elastic caching system on DM is challenging since accessing cached objects with CPU-bypass remote memory accesses hinders the execution of caching algorithms. Moreover, the elastic changes of compute and memory resources on DM affect the access patterns of cached data, compromising the hit rates of caching algorithms. We design Ditto, the first caching system on DM, to address these challenges. Ditto first proposes a client-centric caching framework to efficiently execute various caching algorithms in the compute pool of DM, relying only on remote memory accesses. Then, Ditto employs a distributed adaptive caching scheme that adaptively switches to the best-fit caching algorithm in real-time based on the performance of multiple caching algorithms to improve cache hit rates. Our experiments show that Ditto effectively adapts to the changing resources on DM and outperforms the state-of-the-art caching systems by up to 3.6× in real-world workloads and 9× in YCSB benchmarks.

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I/O Deduplication

Cited by 173 publications

References 19 publications

A data grouping model based on cache transaction for unstructured data storage systems

A data grouping model based on cache transaction for unstructured data storage systems

Design Tradeoffs of SSDs

Ditto: An Elastic and Adaptive Memory-Disaggregated Caching System

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