VLDB 2026 Research / reviewers in the wild / expert

Anne O'Donnell

dblp:91/7785 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2011
—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
Hardware reliability and fault tolerance · 50% Hardware accelerators and domain-specific architectures · 50%
Computer graphics and multimedia
1 paper
Image and video processing · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Hardware accelerators and domain-specific architectures › machine learning accelerator › neural network accelerator › convolution acceleration
convolution accelerator		 0.112011
Offset DMR: A Low Overhead Soft Error Detection and Correction Technique for Transform-Based Convolution · IEEE Trans. Computers 2011
Hardware reliability and fault tolerance
soft errors		 0.112011
Offset DMR: A Low Overhead Soft Error Detection and Correction Technique for Transform-Based Convolution · IEEE Trans. Computers 2011

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

triple modular redundancy comparison · 0.2radix-2 FFT · 0.2
YearPublicationVenuePosition
2011 Offset DMR: A Low Overhead Soft Error Detection and Correction Technique for Transform-Based Convolution
abstract
A novel concurrent soft error detection and correction scheme is introduced for parallel hardware implementations of transform-based convolution. The proposed technique is based on the structure of radix-2 Fast Fourier Transforms (FFT) of length 2nwhere n is an integer. The scheme can provide up to 100 percent detection and correction of isolated single soft errors in the convolution at the cost of little more than double the system area, rather than triple, as is required when using conventional Triple Modular Redundancy (TMR).
Pedro Reviriego, Chris J. Bleakley, Juan Antonio Maestro, Anne O'Donnell
 IEEE Trans. Computers4
2009 Soft error detection and correction for FFT based convolution using different block lengths
abstract
The structure of radix-2 Fast Fourier Transforms of length 2nwhere n is an integer is used to propose a new soft error detection and correction scheme for transform based convolution. The scheme can provide up to 100% detection and correction of isolated soft errors for, in many cases, approximately double the original system cost in terms of area and/or computational complexity. This is a substantial reduction when compared with conventional Triple Modular Redundancy. The method can be used for both hardware and software implementations of transform-based convolution.
Pedro Reviriego, Juan Antonio Maestro, Anne O'Donnell, Chris J. Bleakley
 IOLTS3