ReCA: An Efficient Reconfigurable Cache Architecture for Storage Systems with Online Workload Characterization

In recent years, Solid-State Drives (SSDs) have gained tremendous attention in computing and storage systems due to significant performance improvement over Hard DiskDrives (HDDs). The cost per capacity of SSDs, however, prevents them from entirely replacing HDDs in such systems. One approach to eff...

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Vydáno v:IEEE transactions on parallel and distributed systems Ročník 29; číslo 7; s. 1605 - 1620
Hlavní autoři: Salkhordeh, Reza, Ebrahimi, Shahriar, Asadi, Hossein
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.07.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Cache storage
Caching
Computer architecture
Configurations
Data storage
data storage systems
Disk drives
endurance
Fatigue limit
Hard disks
I/O caching
Linux
Metadata
On-line systems
Performance enhancement
Performance evaluation
Reconfiguration
Runtime
Solid state devices
Solid-state drives
Storage systems
System effectiveness
Workload
Workloads
ISSN:1045-9219, 1558-2183
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Abstract In recent years, Solid-State Drives (SSDs) have gained tremendous attention in computing and storage systems due to significant performance improvement over Hard DiskDrives (HDDs). The cost per capacity of SSDs, however, prevents them from entirely replacing HDDs in such systems. One approach to effectively take advantage of SSDs is to use them as a caching layer to store performance critical data blocks in order to reduce the number of accesses to HDD-based disk subsystem. Due to characteristics of Flash-based SSDs such as limited write endurance and long latency on write operations, employing caching algorithms at the Operating System (OS) level necessitates to take such characteristics into consideration. Previous OS-level caching techniques are optimized towards only one type of application, which affects both generality and applicability. In addition, they are not adaptive when the workload pattern changes over time. This paper presents an efficient Reconfigurable Cache Architecture (ReCA) for storage systems using a comprehensive workload characterization to find an optimal cache configuration for I/O intensive applications. For this purpose, we first investigate various types of I/O workloads and classify them into five major classes. Based on this characterization, an optimal cache configuration is presented for each class of workloads. Then, using the main features of each class, we continuously monitor the characteristics of an application during system runtime and the cache organization is reconfigured if the application changes from one class to another class of workloads. The cache reconfiguration is done online and workload classes can be extended to emerging I/O workloads in order to maintain its efficiency with the characteristics of I/O requests. Experimental results obtained by implementing ReCA in a 4U rackmount server with SATA 6Gb/s disk interfaces running Linux 3.17.0 show that the proposed architecture improves performance and lifetime up to 24 and 33 percent, respectively.
AbstractList In recent years, Solid-State Drives (SSDs) have gained tremendous attention in computing and storage systems due to significant performance improvement over Hard DiskDrives (HDDs). The cost per capacity of SSDs, however, prevents them from entirely replacing HDDs in such systems. One approach to effectively take advantage of SSDs is to use them as a caching layer to store performance critical data blocks in order to reduce the number of accesses to HDD-based disk subsystem. Due to characteristics of Flash-based SSDs such as limited write endurance and long latency on write operations, employing caching algorithms at the Operating System (OS) level necessitates to take such characteristics into consideration. Previous OS-level caching techniques are optimized towards only one type of application, which affects both generality and applicability. In addition, they are not adaptive when the workload pattern changes over time. This paper presents an efficient Reconfigurable Cache Architecture (ReCA) for storage systems using a comprehensive workload characterization to find an optimal cache configuration for I/O intensive applications. For this purpose, we first investigate various types of I/O workloads and classify them into five major classes. Based on this characterization, an optimal cache configuration is presented for each class of workloads. Then, using the main features of each class, we continuously monitor the characteristics of an application during system runtime and the cache organization is reconfigured if the application changes from one class to another class of workloads. The cache reconfiguration is done online and workload classes can be extended to emerging I/O workloads in order to maintain its efficiency with the characteristics of I/O requests. Experimental results obtained by implementing ReCA in a 4U rackmount server with SATA 6Gb/s disk interfaces running Linux 3.17.0 show that the proposed architecture improves performance and lifetime up to 24 and 33 percent, respectively.
Author Ebrahimi, Shahriar
Asadi, Hossein
Salkhordeh, Reza
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  fullname: Asadi, Hossein
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  organization: Dept. of Comput. Eng., Sharif Univ. of Technol., Tehran, Iran
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Snippet In recent years, Solid-State Drives (SSDs) have gained tremendous attention in computing and storage systems due to significant performance improvement over...
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SubjectTerms Cache storage
Caching
Computer architecture
Configurations
Data storage
data storage systems
Disk drives
endurance
Fatigue limit
Hard disks
I/O caching
Linux
Metadata
On-line systems
Performance enhancement
Performance evaluation
Reconfiguration
Runtime
Solid state devices
Solid-state drives
Storage systems
System effectiveness
Workload
Workloads
Title ReCA: An Efficient Reconfigurable Cache Architecture for Storage Systems with Online Workload Characterization
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