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
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Proceedings ArticleDOI
Design and Performance Evaluation of Approximate Floating-Point Multipliers
TL;DR: It is shown that the proposed approximate single precision FP multiplier design reduces power consumption, area and delay by up to 61, 55, and 49% respectively compared with its exact counterpart while incurring in a moderate error.
Journal ArticleDOI
Hybrid Partial Product-based High-Performance Approximate Recursive Multipliers
TL;DR: In this brief, hybrid partial product-based building blocks are proposed by considering the probability distribution of the input operands and an efficient hardware implementation of approximate 4×4 multipliers is achieved, while maintaining the required accuracy.
Journal ArticleDOI
Modeling and analysis of fault tolerant multistage interconnection networks
TL;DR: It is shown that performance degradation due to fault tolerance is graceful while performance degradation without fault recovery is unacceptable, and new performance models are developed and used to evaluate the compound effect of fault tolerant operation on the overall throughput and delay.
Proceedings ArticleDOI
New SRAM Cell Design for Low Power and High Reliability Using 32nm Independent Gate FinFET Technology
TL;DR: A new 8T (8 transistors) SRAM structure that reduces dynamic power for the write operation and achieves a wider SNM (static noise margin) at the expense of 2% leakage power and 3% write delay increase.
Proceedings ArticleDOI
Combining Restoring Array and Logarithmic Dividers into an Approximate Hybrid Design
TL;DR: A new design of an approximate hybrid divider (AXHD), which combines the restoring array and the logarithmic dividers to achieve an excellent tradeoff between accuracy and hardware performance is proposed.