Integrating flash-based SSDs into the storage stack

Appuswamy, Raja; Moolenbroek, David C. van; Tanenbaum, Andrew S.

doi:10.1109/msst.2012.6232365

Cited by 21 publications

(15 citation statements)

References 7 publications

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“…In order to take advantage of the merits of both HDDs and SSDs, several studies from EMC 2 , Facebook, FusionIO, Mercury, and VMware [4,9,13,16,19,25,26,28,30,33,36,37,42,49] employ high-performance SSDs as a caching layer for high-capacity HDDs in storage systems (as shown in Fig. 1).…”

Section: Introductionmentioning

confidence: 99%

ECI-Cache

Ahmadian

Mutlu

Asadi

2018

Proc. ACM Meas. Anal. Comput. Syst.

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In recent years, high interest in using Virtual Machines (VMs) in data centers and Cloud computing has significantly increased the demand for high-performance data storage systems. A straightforward approach to provide a high performance storage system is using Solid-State Drives (SSDs). Inclusion of SSDs in storage systems, however, imposes significantly higher cost compared to Hard Disk Drives (HDDs). Recent studies suggest using SSDs as a caching layer for HDD-based storage subsystems in virtualization platforms. Such studies neglect to address the endurance and cost of SSDs, which can significantly affect the efficiency of I/O caching. Moreover, previous studies only configure the cache size to provide the required performance level for each VM, while neglecting other important parameters such as cache write policy and request type, which can adversely affect both performance-per-cost and endurance.In this paper, we present a new high-Endurance and Cost-efficient I/O Caching (ECI-Cache) scheme for virtualized platforms, which can significantly improve both the performance-per-cost and endurance of storage subsystems as opposed to previously proposed I/O caching schemes. Unlike traditional I/O caching schemes which allocate cache size only based on reuse distance of accesses, we propose a new metric, Useful Reuse Distance (URD), which considers the request type in reuse distance calculation, resulting in improved performance-per-cost and endurance for the SSD cache. Via online characterization of workloads and using URD, ECI-Cache partitions the SSD cache across VMs and is able to dynamically adjust the cache size and write policy for each VM. To evaluate the proposed scheme, we have implemented ECI-Cache in an open source hypervisor, QEMU (version 2.8.0), on a server running the CentOS 7 operating system (kernel version 3.10.0-327). Experimental results show that our proposed scheme improves the performance, performanceper-cost, and endurance of the SSD cache by 17%, 30% and 65%, respectively, compared to the state-of-the-art dynamic cache partitioning scheme. ACM Reference Format:Saba Ahmadian, Onur Mutlu, and Hossein Asadi. 2018. ECI-Cache: A High-Endurance and Cost-Efficient I/O Caching Scheme for Virtualized Platforms. S. Ahmadian et al.delivering the desired performance for each VM. In addition, virtualization provides system isolation where each VM has access only to its own resources. In a virtualized platform, shown in Fig. 1, the resource allocation of each VM is managed by a hypervisor. By employing various modules such as a VM scheduler and a memory and network manager, the hypervisor orchestrates the sharing of resources between VMs according to their demand, in order to maximize the overall performance provided by the server (and this maximizes performance-per-cost by enabling the use of a smaller number of physical servers than one for each VM) [51,53]. With increasing HDD HDD HDD Memory CPU Hardware SSD SSD RAID Controller Cache Module Storage Subsystem CPU Memory VM-1 Hypervisor Memory Manager...

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Section: Introductionmentioning

confidence: 99%

ECI-Cache

Ahmadian

Mutlu

Asadi

2018

Proc. ACM Meas. Anal. Comput. Syst.

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“…In hierarchical storage systems, data migration is the key to offering a high I/O performance of fast storage hardware at the cost of slow storage hardware (Anderson et al, 2001). Most existing work focuses mainly on migration between HDD and SSD (Cheong et al, 2011;Appuswamy et al, 2012), including topics such as migration granularity, data heat identification, static data placement, and dynamic data migration. Many papers have leveraged the block as the unit of data migration and data-hotness identification (Hitachi, 2010;Chen et al, 2011).…”

Section: Hierarchical Storage System and Data Migrationmentioning

confidence: 99%

ONFS: a hierarchical hybrid file system based on memory, SSD, and HDD for high performance computers

Liu

Yu³

et al. 2017

Frontiers Inf Technol Electronic Eng

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With supercomputers developing towards exascale, the number of compute cores increases dramatically, making more complex and larger-scale applications possible. The input/output (I/O) requirements of large-scale applications, workflow applications, and their checkpointing include substantial bandwidth and an extremely low latency, posing a serious challenge to high performance computing (HPC) storage systems. Current hard disk drive (HDD) based underlying storage systems are becoming more and more incompetent to meet the requirements of next-generation exascale supercomputers. To rise to the challenge, we propose a hierarchical hybrid storage system, on-line and near-line file system (ONFS). It leverages dynamic random access memory (DRAM) and solid state drive (SSD) in compute nodes, and HDD in storage servers to build a three-level storage system in a unified namespace. It supports portable operating system interface (POSIX) semantics, and provides high bandwidth, low latency, and huge storage capacity. In this paper, we present the technical details on distributed metadata management, the strategy of memory borrow and return, data consistency, parallel access control, and mechanisms guiding downward and upward migration in ONFS. We implement an ONFS prototype on the TH-1A supercomputer, and conduct experiments to test its I/O performance and scalability. The results show that the bandwidths of single-thread and multi-thread 'read'/'write' are 6-fold and 5-fold better than HDD-based Lustre, respectively. The I/O bandwidth of data-intensive applications in ONFS can be 6.35 times that in Lustre.

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“…In addition to the hardware integration method, two widely used software management methods are used for such heterogeneous storages . One utilizes SSDs as the cache for mechanical disks, and the other treats SSDs and mechanical disks as peers.…”

Section: Backround and Related Workmentioning

confidence: 99%

“…Because the interception was performed at the bottom of the storage hierarchy, the caching effects in the kernel have been filtered out. Thus, the collected access statistics reflect the real storage workload .…”

Section: Design and Implementationmentioning

confidence: 99%

Profit data caching and hybrid disk-aware Completely Fair Queuing scheduling algorithms for hybrid disks

Chang

Liao

Chang

et al. 2014

Softw. Pract. Exper.

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SUMMARYRecently, a hybrid disk drive that integrates a small amount of flash memory within a mechanical drive has received significant attention. The hybrid drive extends the storage hierarchy by using flash memory to cache data from the mechanical disk. Unfortunately, current caching architectures fail to fully exploit the potential of the hybrid drive. Furthermore, current disk input/output (I/O) schedulers are optimized for rotational mechanical disk drives and thus must be re-targeted for the hybrid disk drive. In this paper, we propose a new data caching scheme, called Profit Caching, for hybrid drives. Profit Caching is a self-optimizing caching algorithm. It considers and seamlessly integrates all possible data characteristics that impact the performance of hybrid drives, including read count, write count, sequentiality, randomness, and recency, to determine the caching policy. Moreover, we propose a hybrid disk-aware Completely Fair Queuing (HA-CFQ) scheduler to avoid unnecessary I/O anticipations of the CFQ scheduler. We have implemented Profit Caching and HA-CFQ scheduler in the Linux kernel. Coupled with a trace-driven simulator, we have also conducted detailed experiments under a variety of workloads. Experimental results show that Profit Caching provides significantly improved performance compared with the previous schemes. In particular, the throughput of Profit Caching outperforms previous Random Access First and FlashCache caching schemes by factors of up to 1.8 and 7.6, respectively. In addition, the HA-CFQ scheduler reduces the total execution time of the CFQ scheduler by up to 1.74%. Finally, the experimental results show that the runtime overhead of Profit Caching is extremely insignificant and can be ignored.

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Integrating flash-based SSDs into the storage stack

Cited by 21 publications

References 7 publications

ECI-Cache

ECI-Cache

ONFS: a hierarchical hybrid file system based on memory, SSD, and HDD for high performance computers

Profit data caching and hybrid disk-aware Completely Fair Queuing scheduling algorithms for hybrid disks

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