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Ben Cutler

dblp:181/1450 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 2Software engineering, systems software and programming languages · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Storage systems · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Storage systems › storage reliability
failure characterization
0.212016
SSD Failures in Datacenters: What, When and Why? · SIGMETRICS 2016
Storage systems
flash and SSD
0.212016
SSD Failures in Datacenters: What, When and Why? · SIGMETRICS 2016
Storage systems › flash and SSD
SSD reliability
0.212016
SSD Failures in Datacenters: What, When and Why? · SIGMETRICS 2016

Methods — techniques the papers use, named apart from their topics

statistical characterization · 0.2field data analysis · 0.2
YearPublicationVenuePosition
2016 SSD Failures in Datacenters: What, When and Why?
abstract
Despite the growing popularity of Solid State Disks (SSDs) in the datacenter, little is known about their reliability characteristics in the field. The little knowledge is mainly vendor supplied, which cannot really help understand how SSD failures can manifest and impact production systems, in order to take appropriate actions. Besides failure data, a detailed characterization requires wide spectrum of data about factors influencing SSD failures, right from provisioning (what models' where and when deployed' etc.) to the operational ones (workloads, read-write intensities, write amplification, etc.). We analyze over half a million SSDs that span multiple generations spread across several datacenters which host a wide range of workloads over nearly 3 years. By studying the diverse set of factors on SSD failures, and their symptoms, our work provides the first look at the what, when and why characteristics of SSD failures in production datacenters.
Iyswarya Narayanan, Di Wang 0003, Myeongjae Jeon, Bikash Sharma, Laura Caulfield, Anand Sivasubramaniam, Ben Cutler, Jie Liu 0001, Badriddine M. Khessib, Kushagra Vaid
SIGMETRICS7
2016 SSD Failures in Datacenters: What? When? and Why?
abstract
Despite the growing popularity of Solid State Disks (SSDs) in the datacenter, little is known about their reliability characteristics in the field. The little knowledge is mainly vendor supplied, and such information cannot really help understand how SSD failures can manifest and impact the operation of production systems, in order to take appropriate remedial measures. Besides actual failure data and the symptoms exhibited by SSDs before failing, a detailed characterization effort requires wide set of data about factors influencing SSD failures, right from provisioning factors to the operational ones. This paper presents an extensive SSD failure characterization by analyzing a wide spectrum of data from over half a million SSDs that span multiple generations spread across several datacenters which host a wide spectrum of workloads over nearly 3 years. By studying the diverse set of design, provisioning and operational factors on failures, and their symptoms, our work provides the first comprehensive analysis of the what, when and why characteristics of SSD failures in production datacenters.
Iyswarya Narayanan, Di Wang 0003, Myeongjae Jeon, Bikash Sharma, Laura Caulfield, Anand Sivasubramaniam, Ben Cutler, Jie Liu 0001, Badriddine M. Khessib, Kushagra Vaid
SYSTOR7