Data cache management using frequency-based replacement

Robinson, John T.; Devarakonda, Murthy V.

doi:10.1145/98457.98523

Cited by 268 publications

(73 citation statements)

References 5 publications

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“…We used the aging-LFU cache replacement policy [33]. The host was a dual socket machine with AMD Opteron 270 dual core processors, each running at 2 GHz and 4 GB memory.…”

Section: A Experimental Setupmentioning

confidence: 99%

Centaur: Host-Side SSD Caching for Storage Performance Control

Koller

Mashtizadeh

Rangaswami

2015

2015 IEEE International Conference on Autonomic Computing

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Abstract-Host-side SSD caches represent a powerful knob for improving and controlling storage performance and improve performance isolation. We present Centaur, as a host-side SSD caching solution that uses cache sizing as a control knob to achieve storage performance goals. Centaur implements dynamically partitioned per-VM caches with per-partition local replacement to provide both lower cache miss rate, better performance isolation and performance control for VM workloads. It uses SSD cache sizing as a universal knob for meeting a variety of workloadspecific goals including per-VM latency and IOPS reservations, proportional share fairness, and aggregate optimizations such as minimizing the average latency across VMs. We implemented Centaur for the VMware ESX hypervisor. With Centaur, times for simultaneously booting 28 virtual desktops improve by 42% relative to a non-caching system and by 18% relative to a unified caching system. Centaur also implements per-VM shares for latency with less than 5% error when running microbenchmarks, and enforces latency and IOPS reservations on OLTP workloads with less than 10% error.

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“…We used the aging-LFU cache replacement policy [33]. The host was a dual socket machine with AMD Opteron 270 dual core processors, each running at 2 GHz and 4 GB memory.…”

Section: A Experimental Setupmentioning

confidence: 99%

Centaur: Host-Side SSD Caching for Storage Performance Control

Koller

Mashtizadeh

Rangaswami

2015

2015 IEEE International Conference on Autonomic Computing

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“…The cache half-life is this window of time between which T1 and T2 can execute before the shared data is evicted from the cache by data used for intermediate task executions. While this model is simpler than the actual complex cache data replacement behavior, it is effective enough to give a realistic representation of cache performance [22].…”

Section: Using Cache-half Life To Drive Cache-aware Metaschedulingmentioning

confidence: 99%

Optimizing Integrated Application Performance with Cache-Aware Metascheduling

Dougherty

White

Kegley

et al. 2011

On the Move to Meaningful Internet Systems: OTM 2011

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Abstract. Integrated applications running in multi-tenant environments are often subject to quality-of-service (QoS) requirements, such as resource and performance constraints. It is hard to allocate resources between multiple users accessing these types of applications while meeting all QoS constraints, such as ensuring users complete execution prior to deadlines. Although a processor cache can reduce the time required for the tasks of a user to execute, multiple task execution schedules may exist that meet deadlines but differ in cache utilization efficiency. Determining which task execution schedules will utilize the processor cache most efficiently and provide the greatest reductions in execution time is hard without jeopardizing deadlines. The work in this paper provides three key contributions to increasing the execution efficiency of integrated applications in multi-tenant environments while meeting QoS constraints. First, we present cache-aware metascheduling, which is a novel approach to modifying system execution schedules to increase cache-hit rate and reduce system execution time. Second, we apply cache-aware metascheduling to 11 simulated software systems to create 2 different execution schedules per system. Third, we empirically evaluate the impact of using cache-aware metascheduling to alter task schedules to reduce system execution time. Our results show that cache-aware metascheduling increases cache performance, reduces execution time, and satisfies scheduling constraints and safety requirements without requiring significant hardware or software changes.

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“…Still they contain enough temporal locality that LRU works reasonably well, but can be outperformed by frequency based strategies [14]. All of the above systems are normally based on fixed size caching units.…”

Section: Caching In Various Contextsmentioning

confidence: 99%

Effectiveness of caching in a distributed digital library system

Hollmann

Ardö

Stenström

2007

Journal of Systems Architecture

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Today independent publishers are offering digital libraries with fulltext archives. In an attempt to provide a single user-interface to a large set of archives, the studied Article-Database-Service offers a consolidated interface to a geographically distributed set of archives. While this approach offers a tremendous functional advantage to a user, the fulltext download delays caused by the network and queuing in servers make the user-perceived interactive performance poor. This paper studies how effective caching of articles at the client level can be achieved as well as at intermediate points as manifested by gateways that implement the interfaces to the many fulltext archives. A central research question in this approach is: What is the nature of locality in the user access stream to such a digital library. Based on access logs that drive the simulations, it is shown that client-side caching can result in a 20% hit rate. Even at the gateway level temporal locality is observable, but published replacement algorithms are unable to exploit this temporal locality. Additionally, spatial locality can be exploited by considering loading into cache all articles in an issue, volume, or journal, if a single article is accessed. But our experiments showed that improvement introduced a lot of overhead. Finally, it is shown that the reason for this cache behavior is the long time distance between re-accesses, which makes caching quite unfeasable.

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Data cache management using frequency-based replacement

Cited by 268 publications

References 5 publications

Centaur: Host-Side SSD Caching for Storage Performance Control

Centaur: Host-Side SSD Caching for Storage Performance Control

Optimizing Integrated Application Performance with Cache-Aware Metascheduling

Effectiveness of caching in a distributed digital library system

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