Demo Data from VLDB 2026 / reviewers in the wild / expert
Simone Bettola
dblp:62/6461
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1998
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1 · 1 first-author
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 · 62% Hardware accelerators and domain-specific architectures · 19% Integrated circuit design · 19% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Hardware accelerators and domain-specific architectures › machine learning accelerator
neural network accelerator |
0.0 | 1 | 1998 | High Performance Fault-Tolerant Digital Neural Networks · IEEE Trans. Computers 1998 |
Integrated circuit design › redundant number representation
redundant binary representation |
0.0 | 1 | 1998 | High Performance Fault-Tolerant Digital Neural Networks · IEEE Trans. Computers 1998 |
Methods — techniques the papers use, named apart from their topics
three-rail logic · 0.0redundant binary representation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1998 | High Performance Fault-Tolerant Digital Neural NetworksabstractEfficient implementation of neural networks requires high-performance architectures, while VLSI realization for mission-critical applications must include fault tolerance. Contemporaneous solution of such problems has not yet been completely afforded in the literature. This paper focuses both on data representation to support high-performance neural computation and on error detection to provide the basic information for fault tolerance by using the redundant binary representation with a three-rail logic implementation. Costs and performances are evaluated referring to multilayered feed-forward networks. Simone Bettola, Vincenzo Piuri |
IEEE Trans. Computers | 1 |