Title
Exploiting Intra-Request Slack to Improve SSD Performance.
Abstract
With Solid State Disks (SSDs) offering high degrees of parallelism, SSD controllers place data and direct requests to exploit the maximum offered hardware parallelism. In the quest to maximize parallelism and utilization, sub-requests of a request that are directed to different flash chips by the scheduler can experience differential wait times since their individual queues are not coordinated and load balanced at all times. Since the macro request is considered complete only when its last sub-request completes, some of its sub-requests that complete earlier have to necessarily wait for this last sub-request. This paper opens the door to a new class of schedulers to leverage such slack between sub-requests in order to improve response times. Specifically, the paper presents the design and implementation of a slack-enabled re-ordering scheduler, called Slacker, for sub-requests issued to each flash chip. Layered under a modern SSD request scheduler, Slacker estimates the slack of each incoming sub-request to a flash chip and allows them to jump ahead of existing sub-requests with sufficient slack so as to not detrimentally impact their response times. Slacker is simple to implement and imposes only marginal additions to the hardware. Using a spectrum of 21 workloads with diverse read-write characteristics, we show that Slacker provides as much as 19.5%, 13% and 14.5% improvement in response times, with average improvements of 12%, 6.5% and 8.5%, for write-intensive, read-intensive and read-write balanced workloads, respectively.
Year
DOI
Venue
2017
10.1145/3037697.3037728
ASPLOS
Keywords
Field
DocType
SSD,Scheduling,Intra-request slack
Load balancing (computing),Scheduling (computing),Computer science,Queue,Parallel computing,Real-time computing,Chip,Exploit,Macro,Solid-state
Conference
Volume
Issue
ISSN
52
4
0362-1340
Citations 
PageRank 
References 
10
0.55
17
Authors
6
Name
Order
Citations
PageRank
Nima Elyasi1141.99
Mohammad Arjomand227320.31
Anand Sivasubramaniam34485291.86
Mahmut T. Kandemir47371568.54
Chita R. Das5146780.03
Myoung-Soo Jung631425.09