A Unified Approach to the Performance Analysis of Caching Systems

Garetto, Michele; Leonardi, E.; Martina, Valentina

doi:10.1145/2896380

Cited by 123 publications

(147 citation statements)

References 39 publications

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“…In this paper we use the expression Che's approximation to denote the possibility to approximate a replacement policy with an opportunely tuned TTL-policy. This approach has been shown to be very accurate [15,16]. More recently, the practical use of TTL-policies has been advocated because of their flexibility [7,6].…”

Section: Background and Related Workmentioning

confidence: 99%

Cache policies for linear utility maximization

Neglia

Carra²,

Michiardi³

2017

IEEE INFOCOM 2017 - IEEE Conference on Computer Communications

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Cache policies to minimize the content retrieval cost have been studied through competitive analysis when the miss costs are additive and the sequence of content requests is arbitrary. More recently, a cache utility maximization problem has been introduced, where contents have stationary popularities and utilities are strictly concave in the hit rates. This paper bridges the two formulations, considering linear costs and content popularities. We show that minimizing the retrieval cost corresponds to solving an online knapsack problem, and we propose new dynamic policies inspired by simulated annealing, including DynqLRU, a variant of qLRU. For such policies we prove asymptotic convergence to the optimum under the characteristic time approximation. In a real scenario, popularities vary over time and their estimation is very difficult. DynqLRU does not require popularity estimation, and our realistic, trace-driven evaluation shows that it significantly outperforms state-of-the-art policies, with up to 45% cost reduction. Notice: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.

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Section: Background and Related Workmentioning

confidence: 99%

Cache policies for linear utility maximization

Neglia

Carra²,

Michiardi³

2017

IEEE INFOCOM 2017 - IEEE Conference on Computer Communications

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“…The accuracy of modelling LRUbased caching techniques is discussed in [54]. Extension and generalization of such techniques is investigated in [55], where temporal locality is included in the suggested model. The behavior of LRU and First-In First-Out (FIFO) policies can also be predicted using the low-complexity method presented in [40].…”

Section: Previous Studiesmentioning

confidence: 99%

An Analytical Model for Performance and Lifetime Estimation of Hybrid DRAM-NVM Main Memories

Salkhordeh

Mutlu

Asadi

2019

IEEE Trans. Comput.

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Emerging Non-Volatile Memories (NVMs) have promising advantages (e.g., lower idle power, higher density, and nonvolatility) over the existing predominant main memory technology, DRAM. Yet, NVMs also have disadvantages (e.g., longer latencies, higher active power, and limited endurance). System architects are therefore examining hybrid DRAM-NVM main memories to enable the advantages of NVMs while avoiding the disadvantages as much as possible. Unfortunately, the hybrid memory design space is very large and complex due to the existence of very different types of NVMs and their rapidly-changing characteristics. Therefore, optimization of performance and lifetime of hybrid memory based computing platforms and their experimental evaluation using traditional simulation methods can be very time-consuming and sometimes even impractical. As such, it is necessary to develop a fast and flexible analytical model to estimate the performance and lifetime of hybrid memories on various workloads. This paper presents an analytical model for hybrid memories based on Markov decision processes. The proposed model estimates the hit ratio and lifetime for various configurations of DRAM-NVM hybrid main memories. Our model also provides accurate estimation of the effect of data migration policies on the hybrid memory hit ratio (i.e., percentage of accesses supplied by either DRAM or NVM), one of the most important factors in hybrid memory performance and lifetime. Such an analytical model can aid designers to tune hybrid memory configurations to improve performance and/or lifetime. We present several optimizations that make our model more efficient while maintaining its accuracy. Our experimental evaluations conducted using the PARSEC benchmark suite show that the proposed model (a) accurately predicts the hybrid memory hit ratio compared to the state-of-the-art hybrid memory simulators with an average (maximum) error of 4.61% (13.6%) on a commodity server (equipped with 192GB main memory and quad-core Xeon processor), (b) accurately estimates the NVM lifetime with an average (maximum) error of 2.93% (8.8%), and (c) is on average (up to) 4x (10x) faster than conventional state-of-the-art simulation platforms for hybrid memories.

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“…TTL caches have found their place in theory as a tool for analyzing capacity based caches [9], [12], [13], starting from characteristic time approximation of LRU caches [14], [15]. Recently, its generalizations [5], [18] have commented on its wider applicability.…”

Section: Related Workmentioning

confidence: 99%

Adaptive TTL-Based Caching for Content Delivery

Basu

Sundarrajan

Ghaderi

et al. 2017

Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems

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Abstract-Content Delivery Networks (CDNs) cache and serve a majority of the user-requested content on the Internet. Designing caching algorithms that automatically adapt to the heterogeneity, burstiness, and non-stationary nature of real-world content requests is a major challenge and is the focus of our work. While there is much work on caching algorithms for stationary request traffic, the work on non-stationary request traffic is very limited. Consequently, most prior models are inaccurate for non-stationary production CDN traffic. We propose two TTLbased caching algorithms that provide provable performance guarantees for request traffic that is bursty and non-stationary. The first algorithm called d-TTL dynamically adapts a TTL parameter using stochastic approximation. Given a feasible target hit rate, we show that d-TTL converges to its target value for a general class of bursty traffic that allows Markov dependence over time and non-stationary arrivals. The second algorithm called f-TTL uses two caches, each with its own TTL. The firstlevel cache adaptively filters out non-stationary traffic, while the second-level cache stores frequently-accessed stationary traffic. Given feasible targets for both the hit rate and the expected cache size, f-TTL asymptotically achieves both targets. We evaluate both d-TTL and f-TTL using an extensive trace containing more than 500 million requests from a production CDN server. We show that both d-TTL and f-TTL converge to their hit rate targets with an error of about 1.3%. But, f-TTL requires a significantly smaller cache size than d-TTL to achieve the same hit rate, since it effectively filters out non-stationary content.

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A Unified Approach to the Performance Analysis of Caching Systems

Cited by 123 publications

References 39 publications

Cache policies for linear utility maximization

Cache policies for linear utility maximization

An Analytical Model for Performance and Lifetime Estimation of Hybrid DRAM-NVM Main Memories

Adaptive TTL-Based Caching for Content Delivery

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