scispace - formally typeset
F

Fabrizio Lombardi

Researcher at Northeastern University

Publications -  677
Citations -  12743

Fabrizio Lombardi is an academic researcher from Northeastern University. The author has contributed to research in topics: Fault detection and isolation & Redundancy (engineering). The author has an hindex of 51, co-authored 639 publications receiving 10357 citations. Previous affiliations of Fabrizio Lombardi include Helsinki University of Technology & Fudan University.

Papers
More filters
Journal ArticleDOI

Design of a Nonvolatile 7T1R SRAM Cell for Instant-on Operation

TL;DR: This paper presents a novel NVSRAM circuit for “Instant-on” operation and evaluates its performance at nanometric feature sizes and offers better nonvolatile performance (in terms of operations such as “Store,” “Power-down,’ and “Restore”) when compared with existingnonvolatile cells.
Journal ArticleDOI

Tile-based QCA design using majority-like logic primitives

TL;DR: Using a coherence vector simulation engine, it is shown that the 3 × 3 grid offers versatile logic operation and different combinational functions such as majority-like and wire crossing are obtained using these tiles.
Journal ArticleDOI

Design and analysis of a 32nm PVT tolerant CMOS SRAM cell for low leakage and high stability

TL;DR: A novel nine transistor (9T) CMOSSRAM cell design at 32nm feature size is presented to improve the stability, power dissipation, and delay of the conventional SRAM cell along with detailed comparisons with other designs.
Proceedings ArticleDOI

Clocking and Cell Placement for QCA

TL;DR: A significant reduction in the longest line length permits a fast timing and efficient pipelining to occur, while guaranteeing kink-free behavior in switching.
Proceedings ArticleDOI

Testing memory modules in SRAM-based configurable FPGAs

TL;DR: The issues involved in testing memory modules (configured as LUTs and RAMs) in FPGAs are studied and new algorithms are proposed as this scenario is substantially different from traditional memory testing.