Using MEMS-based storage in disk arrays

FAST, pp.7-7, (2003)

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Abstract

Current disk arrays, the basic building blocks of high-performance storage systems, are built around two memory technologies: magnetic disk drives, and non-volatile DRAM caches. Disk latencies are higher by six orders of magnitude than non-volatile DRAM access times, but cache costs over 1000 times more per byte. A new storage technology ...More

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Introduction
  • Disk arrays [16] are the main building blocks used to satisfy the performance and dependability requirements of current high-end storage systems.
  • A disk array consists of a large number of disk drives, partially used to store redundant data that will allow transparent recovery from disk failures; controllers that interface with client hosts and maintain redundant data; and large battery-backed, non-volatile RAM (NVRAM) caches that allow optimizations such as prefetching, write-behind, and background destaging to mitigate the effects of high disk latencies.
  • Email: The access latency gap between disk and NVRAM is currently almost six orders of magnitude (10 ms vs 50 ns), and is widening by about 50% per year.
  • NVRAM costs about three orders of magnitude more per byte than disk drives.
  • Battery packs are cumbersome, as they must be capable of supplying enough power for the whole array; they can reach hundreds of pounds in weight and many cubic feet in size
Highlights
  • Disk arrays [16] are the main building blocks used to satisfy the performance and dependability requirements of current high-end storage systems
  • A disk array consists of a large number of disk drives, partially used to store redundant data that will allow transparent recovery from disk failures; controllers that interface with client hosts and maintain redundant data; and large battery-backed, non-volatile RAM (NVRAM) caches that allow optimizations such as prefetching, write-behind, and background destaging to mitigate the effects of high disk latencies
  • The hybrid architectures we have studied include several different data layouts and corresponding IO access policies, in order to determine if the different characteristics of disks and microelectromechanical systems (MEMS) storage can be exploited for better performance
  • Given that most of the architectures we introduced have a higher cost per byte than DiskOnly, it is legitimate to ask what the performance of DiskOnly would be if the extra money spent on MEMS were to be spent on additional disks instead, to get more spindles in the backend
  • If the data is striped over all disks, there are two potential performance advantages: more disk arms imply more potential parallelism, and partially-empty disks incur shorter seeks. To address this question we studied the Isocost-X architectures, i.e., instances of DiskOnly in which the number of disk drives is increased until the cost matches that of a MEMSdisk architecture, assuming that the per-byte cost ratio of MEMS storage to disk is latency of 0.7–1.1ms
  • We examined several possible placements for the MEMS storage in the disk array by (1) replacing all the disks with MEMS storage, (2) replacing the NVRAM cache with MEMS storage, and (3) replacing half the disks with MEMS storage
Results
  • Since MEMS-based devices have the potential to affect both the throughput and latency characteristics of disk arrays, the authors consider both performance metrics.
  • If the data is striped over all disks, there are two potential performance advantages: more disk arms imply more potential parallelism, and partially-empty disks incur shorter seeks
  • To address this question the authors studied the Isocost-X architectures, i.e., instances of DiskOnly in which the number of disk drives is increased until the cost matches that of a MEMSdisk architecture, assuming that the per-byte cost ratio of MEMS storage to disk is latency of 0.7–1.1ms
Conclusion
  • Conclusions and future work

    The authors explored the performance and the performance/cost implications of incorporating MEMS-based storage into disk array architectures.
  • Replacing the disks with MEMS storage improves performance substantially in terms of latency and throughput depending on workload, but at high cost.
  • Performance/cost, based on the average throughput of the trace workloads used, ranges between 2–7 times that of DiskOnly, depending on the MEMS/disk cost ratio.
  • The performance/cost of LogDisk is similar to that of purely MEMS-based arrays, and better than DiskOnly by a factor of 2.5–5.5, depending on the MEMS/disk cost ratio.
  • Average latency is substantially lower than DiskOnly for all the hybrid architectures — by a factor of between 4 and 16 for the trace workloads studied here
Tables
  • Table1: MEMS-chip parameters
Download tables as Excel
Related work
  • This paper combines the use of MEMS storage devices with several different redundancy schemes and layouts in efficient storage array architectures. The physical characteristics and performance of MEMS-based storage devices are discussed in several papers from the CMU Parallel Data Laboratory [3, 20, 8].

    The use of redundant data layouts for reliability, load balance and improved performance is well established [1, 2, 16], and these are commonly used in modern disk arrays. In most such layouts, the performance of the disk is limited by the disk head seek time and rotational delays, particularly for workloads with small, nonsequential I/Os. Several mechanisms have been proposed to ameliorate the impact of positioning time for writes. A write cache can substantially reduce the number of disk writes and the perceived delay for writes [22, 9]; however, for reliability, these caches must generally use expensive NVRAM, ideally in a redundant configuration.
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