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Author

Luca Sterpone

Other affiliations: Instituto Politécnico Nacional
Bio: Luca Sterpone is an academic researcher from Polytechnic University of Turin. The author has contributed to research in topics: Fault injection & Field-programmable gate array. The author has an hindex of 24, co-authored 222 publications receiving 3125 citations. Previous affiliations of Luca Sterpone include Instituto Politécnico Nacional.


Papers
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Proceedings ArticleDOI
03 Oct 2012
TL;DR: The overall target of the research is the development of a design methodology for highly reliable systems realized on reconfigurable platforms based on a System-on-Programmable Chip (SoPC), as discussed in the next section.
Abstract: While the shrinking of minimum dimensions of integrated circuits till tenths of nanometers allows the integration of millions of gates on the single chip, it also implies the growth of the importance of effects that could reduce the reliability of circuits. In particular, the reduced integration step, the reduced supply voltage that lowers the noise immunity, the growing power needs, the eventual integration of both digital and analog circuits on the same chip and the highly growing of radiation sensitivity [1], [2], [3] require an accurate evaluation of possible reliability reduction for the occurrence of: • permanent faults due to the aging of device materials [4], the interruptions of metal interconnections due to electromigration [5] or the crack of the insulation oxide of transistor [6]; • transient faults, known as Single Event Effects (SEE), which are much more likely than in the past due to the reduced transistors' sizes [3]: in particular new technology devices are more prone to crosstalk in the interconnects and to radiation effects.

5 citations

Proceedings ArticleDOI
01 Apr 2023
TL;DR: In this article , the authors describe how to correctly specify statistical FIs for Convolutional Neural Networks, and propose a data analysis on the CNN parameters that drastically reduces the number of FIs needed to achieve statistically significant results without compromising the validity of the proposed method.
Abstract: Assessing the reliability of modern devices running CNN algorithms is a very difficult task. Actually, the complexity of the state-of-the-art devices makes exhaustive Fault Injection (FI) campaigns impractical and typically out of the computational capabilities. A possible solution consists of resorting to statistical FI campaigns that allow a reduction in the number of needed experiments by injecting only a carefully selected small part of it. Under specific hypothesis, statistical FIs guarantee an accurate picture of the problem, albeit selecting a reduced sample size. The main problems today are related to the choice of the sample size, the location of the faults, and the correct understanding of the statistical assumptions. The intent of this paper is twofold: first, we describe how to correctly specify statistical FIs for Convolutional Neural Networks; second, we propose a data analysis on the CNN parameters that drastically reduces the number of FIs needed to achieve statistically significant results without compromising the validity of the proposed method. The methodology is experimentally validated on two CNNs, ResNet-20 and MobileNetV2, and the results show that a statistical FI campaign on about 1.21% and 0.55% of the possible faults, provides very precise information of the CNN reliability. The statistical results have been confirmed by the exhaustive FI campaigns on the same cases of study.

5 citations

Book ChapterDOI
01 Jan 2011
TL;DR: The FPGA architecture based on SRAM configuration memory can be configured in a very reduced time with whatever processor, differently from the antifuse FPGa that could be programmed only a single time.
Abstract: The first FPGA models have been introduced during the 1980s. The first programmable logic, almost similar to the FPGA, is comparable to the first costly programmable devices called programmable logic devices (PLDs) but able to implement a significantly higher amount of logic. Two first categories of devices have been developed: antifuse, consisting of an electrically programmable configuration memory which can be programmed only a single time and FPGA based on a configuration memory with SRAM cells that can be configured. Despite the antifuse devices were initially preferred for the more stability of the configuration memory, at the end of the 1980s, most of the preliminary dependability problems were solved, and the technology based on SRAM has started growing thanks to the volatility of the configuration memory that enables a wide range of applications. The FPGA architecture based on SRAM configuration memory can be configured in a very reduced time with whatever processor, differently from the antifuse FPGA that could be programmed only a single time.

5 citations

Journal ArticleDOI
TL;DR: UA 2 TPG is a static analysis tool for the untestability proof and automatic test pattern generation for SEUs in the configuration memory of SRAM-based FPGA systems based on the model-checking verification technique.

5 citations

Proceedings ArticleDOI
18 Apr 2006
TL;DR: The ReCoM architecture is described and its effectiveness for a digital signal processing benchmark application and its efficient configuration and data memory architecture is presented.
Abstract: Reconfigurable mixed grain (ReCoM) is a novel reconfigurable compute fabric (RCF) architecture based on a mixed-grain reconfigurable array which combines a RISC microprocessor and a reconfigurable hardware for computation-intensive applications. ReCoM comprises a modified RISC microprocessor, a dynamically reconfigurable processing array including reconfigurable cells formed by a 64-bits ALU, look up tables (LUTs), word-level arithmetic units, and an efficient configuration and data memory architecture. This paper describes the ReCoM architecture and presents its effectiveness for a digital signal processing benchmark application

5 citations


Cited by
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Journal ArticleDOI
TL;DR: A comprehensive overview of the current understanding of the physiological roles of EVs is provided, drawing on the unique EV expertise of academia-based scientists, clinicians and industry based in 27 European countries, the United States and Australia.
Abstract: In the past decade, extracellular vesicles (EVs) have been recognized as potent vehicles of intercellular communication, both in prokaryotes and eukaryotes. This is due to their capacity to transfer proteins, lipids and nucleic acids, thereby influencing various physiological and pathological functions of both recipient and parent cells. While intensive investigation has targeted the role of EVs in different pathological processes, for example, in cancer and autoimmune diseases, the EV-mediated maintenance of homeostasis and the regulation of physiological functions have remained less explored. Here, we provide a comprehensive overview of the current understanding of the physiological roles of EVs, which has been written by crowd-sourcing, drawing on the unique EV expertise of academia-based scientists, clinicians and industry based in 27 European countries, the United States and Australia. This review is intended to be of relevance to both researchers already working on EV biology and to newcomers who will encounter this universal cell biological system. Therefore, here we address the molecular contents and functions of EVs in various tissues and body fluids from cell systems to organs. We also review the physiological mechanisms of EVs in bacteria, lower eukaryotes and plants to highlight the functional uniformity of this emerging communication system.

3,690 citations

Journal ArticleDOI
TL;DR: Recent progress in understanding extracellular vesicle biology and the role of extrace cellular vesicles in disease is reviewed, emerging therapeutic opportunities are discussed and the associated challenges are considered.
Abstract: Within the past decade, extracellular vesicles have emerged as important mediators of intercellular communication, being involved in the transmission of biological signals between cells in both prokaryotes and higher eukaryotes to regulate a diverse range of biological processes. In addition, pathophysiological roles for extracellular vesicles are beginning to be recognized in diseases including cancer, infectious diseases and neurodegenerative disorders, highlighting potential novel targets for therapeutic intervention. Moreover, both unmodified and engineered extracellular vesicles are likely to have applications in macromolecular drug delivery. Here, we review recent progress in understanding extracellular vesicle biology and the role of extracellular vesicles in disease, discuss emerging therapeutic opportunities and consider the associated challenges.

2,507 citations

Journal ArticleDOI
16 Mar 2012-Cell
TL;DR: Emerging principles of miRNA regulation of stress signaling pathways are reviewed and applied to the authors' understanding of the roles of miRNAs in disease.

1,491 citations

Journal ArticleDOI
TL;DR: The results show that atheroprotective stimuli induce communication between endothelial cells and SMCs through an miRNA- and extracellular-vesicle-mediated mechanism and that this may comprise a promising strategy to combat atherosclerosis.
Abstract: The shear-responsive transcription factor Kruppel-like factor 2 (KLF2) is a critical regulator of endothelial gene expression patterns induced by atheroprotective flow. As microRNAs (miRNAs) post-transcriptionally control gene expression in many pathogenic and physiological processes, we investigated the regulation of miRNAs by KLF2 in endothelial cells. KLF2 binds to the promoter and induces a significant upregulation of the miR-143/145 cluster. Interestingly, miR-143/145 has been shown to control smooth muscle cell (SMC) phenotypes; therefore, we investigated the possibility of transport of these miRNAs between endothelial cells and SMCs. Indeed, extracellular vesicles secreted by KLF2-transduced or shear-stress-stimulated HUVECs are enriched in miR-143/145 and control target gene expression in co-cultured SMCs. Extracellular vesicles derived from KLF2-expressing endothelial cells also reduced atherosclerotic lesion formation in the aorta of ApoE(-/-) mice. Combined, our results show that atheroprotective stimuli induce communication between endothelial cells and SMCs through an miRNA- and extracellular-vesicle-mediated mechanism and that this may comprise a promising strategy to combat atherosclerosis.

1,182 citations

Journal ArticleDOI
TL;DR: The information synthesized is expected to open new avenues for a large scale use of insect products as animal feed, and the levels of Ca and fatty acids in insect meals can be enhanced by manipulation of the substrate on which insects are reared.

1,068 citations