High Performance & Low Latency in Solid-State DrivesThrough Redundancy

Dimitris Skourtis, Scott Brandt, Carlos MaltzahnUniversity of California, Santa Cruz

{skourtis, scott, carlosm}@cs.ucsc.edu

Abstract

Solid-state drives are becoming increasingly popular inenterprise storage systems, playing the role of largecaches and permanent storage. Although SSDs providefaster random access than hard-drives, their performanceis especially workload-dependent and can be inconsistentto the point that it becomes worse than that of hard-drives(e.g., taking more than 100ms for a single read).

Many systems with mixed workloads have low latencyrequirements for reads and in such cases SSD inconsis-tencies become a problem. We present a solution thatis based on redundancy and provides high performance,low latency and consistent read performance, as well asfault-tolerance, making it an alternative RAID-like de-sign for solid-state drives.

Design and Evaluation

Solid-state drives have fast random access and often ex-hibit high performance. However, depending on theircurrent and past workloads their performance can de-grade quickly. For example, performing a mixture oflarge sequential and random writes over a large part ofa drive’s logical range can lead to high latencies. Thisis often due to the garbage collector not being able tokeep up leading to what is known as internal fragmenta-tion [1]. In such cases, mixing reads with writes leadsto write-induced blocking events. Although such eventsmay directly block less than 5% of the requests, they canaccount for a significant proportion of the device’s time,e.g., 50%, leading to high latencies for queued requests.

We propose a new design based on redundancy thatprovides consistent performance and minimal latency forreads by physically isolating reads from writes. In otherwords we nearly eliminate the extra latency that readshave to pay due to writes, which is crucial for many ap-plications with low latency requirements. Through thatseparation we minimize the read/write interference and

SSD 1Read mode

Writes from previous period

WritesReads

Writes of current periodCache

SSD 2Write mode

Figure 1: Each of the two drives is either performingreads or writes at any given time. While the first drive isreading, the other drive performs the writes of the previ-ous period - before the drives switched roles.

have the opportunity to further optimize reads and writesseparately. In terms of write performance, unless enoughwrites are synchronous or the system is allowed to beoverloaded, the user conceives write performance as per-fectly consistent. Note that using a single drive and dis-patching reads and writes in batches as in [2], may im-prove the performance under certain workloads and SSDmodels. However, it does not eliminate the frequentblocking events under a generic workload.

Solid-state drive models differ from each other and amethod or heuristic solution working on one SSD maynot work equally well on another. We are interested in anapproach that works across different models. Given twodrives D1 and D2, we propose the separation of readsfrom writes by first sending reads to D1 and writes toD2. After a variable amount of time T � T

min

, the drivesswitch roles with D2 performing writes and D1 reads.When the switch takes place, D2 first performs all thewrites D1 completed that D2 has not, so that the drivesare in sync. If D2 completes syncing and the window

1

(a) Under large requests, the read performance is high and consistent. (b) Small requests also achieve consistent and high read performance.

Figure 2: By physically separating reads from writes we achieve high performance, consistency, and minimal latencyfor both small and large requests.

Figure 3: Using a single drive, the garbage collector can-not keep up, leading to prohibitively high read latenciesand inconsistent performance. Our design solves thisproblem while doubling the read throughput.

is not yet over (t < T

min

,) D2 continues with new writesuntil t � T

min

. In order to enable the above, we placea cache on top of the drives. All new writes first go tothe cache, while the write-drive D

w

is sent the writes thatwere stored in the cache during the previous window. Ofcourse, if there are not enough writes in the cache af-ter the drives are in sync, D

w

may be used to increase theread performance. Finally, at any point in time, the unionof the cache with any of the two drives contains exactlythe same data. Hence, if one drive fails, no data is lost.

We implemented our design and verified that it pro-vides high performance, low latency and read perfor-

mance consistency under mixed workloads. For our ex-periments we used two 250GB Intel 510 SSDs that werepreviously written randomly. Note that although our de-sign includes a cache and therefore cache hits as well asoverwriting data still in cache are possible optimizationswe looked at the worst-case and ignored potential cachehits. Our workloads consist of either small or large re-quests of four types, as shown in Figure 2. From thesame figure we see that reads (1100 per sec) are not af-fected by writes, while writes have a similar performanceas in our write-only experiments (not shown.) On theother hand, without redundancy reads achieve a total av-erage of 525 reads/sec (Figure 3) when given 50% of thedevice time, which is less than half of our method. Mostimportantly the latencies are many times higher as wellas inconsistent, while our approach achieves low read la-tencies consistently.

Besides offering low latency, our design makes it eas-ier to provide efficient QoS for mixed workloads, andthat is part of our current work. In addition, it can becombined with existing configurations such as RAID-01and RAID-10. Finally, we are working on an evaluationunder live workloads, such as databases and VMs.

References[1] CHEN, F., KOUFATY, D. A., AND ZHANG, X. Understanding

intrinsic characteristics and system implications of flash memorybased solid state drives. In Proceedings of the eleventh interna-

tional joint conference on Measurement and modeling of computer

systems (New York, NY, USA, 2009), SIGMETRICS ’09, ACM,pp. 181–192.

[2] PARK, S., AND SHEN, K. Fios: a fair, efficient flash i/o scheduler.In Proceedings of the 10th USENIX conference on File and Stor-

age Technologies (Berkeley, CA, USA, 2012), FAST’12, USENIXAssociation, pp. 13–13.

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