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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
01 Feb 2021
TL;DR: In this article, the authors proposed a new 3D LUT design integrating error detection capabilities, which has been designed on a two-tier IC model improving radiation resiliency by selective upsizing of sensitive transistors.
Abstract: Three-dimensional Integrated Circuits (3-D ICs) have gained much attention as a promising approach to increase IC performance due to their several advantages in terms of integration density, power dissipation, and achievable clock frequencies. However, achieving a 3-D ICs resilient to soft errors resulting from radiation effects is a challenging problem. Traditional Radiation-Hardened-by-Design (RHBD) techniques are costly in terms of area, power, and performance overheads. In this work, we propose a new 3-D LUT design integrating error detection capabilities. The LUT has been designed on a two tiers IC model improving radiation resiliency by selective upsizing of sensitive transistors. Besides, an in-silicon radiation sensor adopting inverters chain has been implemented within the free volume of the 3-D structure. The proposed design shows a 37% reduction in sensitivity to SETs and an effective error detection rate of 83% without introducing any area overhead.
Journal ArticleDOI
TL;DR: In this paper , the authors presented a workflow for real-time detection of signal for help gestures based on two lightweight CNN architectures, dedicated to hand palm detection and hand gesture classification, respectively.
Abstract: In April 2020, by the start of isolation all around the world to counter the spread of COVID-19, an increase in violence against women and kids has been observed such that it has been named The Shadow Pandemic. To fight against this phenomenon, a Canadian foundation proposed the “Signal for Help” gesture to help people in danger to alert others of being in danger, discreetly. Soon, this gesture became famous among people all around the world, and even after COVID-19 isolation, it has been used in public places to alert them of being in danger and abused. However, the problem is that the signal works if people recognize it and know what it means. To address this challenge, we present a workflow for real-time detection of “Signal for Help” based on two lightweight CNN architectures, dedicated to hand palm detection and hand gesture classification, respectively. Moreover, due to the lack of a “Signal for Help” dataset, we create the first video dataset representing the “Signal for Help” hand gesture for detection and classification applications which includes 200 videos. While the hand-detection task is based on a pre-trained network, the classifying network is trained using the publicly available Jesture dataset, including 27 classes, and fine-tuned with the “Signal for Help” dataset through transfer learning. The proposed platform shows an accuracy of 91.25% with a video processing capability of 16 fps executed on a machine with an Intel [email protected] GHz CPU, 31.2 GB memory, and NVIDIA GeForce RTX 2080 Ti GPU, while it reaches 6 fps when running on Jetson Nano NVIDIA developer kit as an embedded platform. The high performance and small model size of the proposed approach ensure great suitability for resource-limited devices and embedded applications which has been confirmed by implementing the developed framework on the Jetson Nano Developer Kit. A comparison between the developed framework and the state-of-the-art hand detection and classification models shows a negligible reduction in the validation accuracy, around 3%, while the proposed model required 4 times fewer resources for implementation, and inference has a speedup of about 50% on Jetson Nano platform, which make it highly suitable for embedded systems. The developed platform as well as the created dataset are publicly available.
Journal ArticleDOI
TL;DR: In this article , the failure rate of different layout solutions of redundancy-based radiation tolerant design is evaluated using fault injection campaigns and proton radiation tests on different radiation-tolerant design implementations.
Proceedings ArticleDOI
01 Apr 2023
TL;DR: The EuFRATE project as discussed by the authors aims to develop and test radiation-hardening methods for telecommunication payloads deployed for Geostationary-Earth Orbit (GEO) using Commercial-Off- The-Shelf Field Programmable Gate Arrays (FPGAs).
Abstract: The EuFRATE project aims to research, develop and test radiation-hardening methods for telecommunication payloads deployed for Geostationary-Earth Orbit (GEO) using Commercial-Off- The-Shelf Field Programmable Gate Arrays (FPGAs). This project is conducted by Argotec Group (Italy) with the collaboration of two partners: Politecnico di Torino (Italy) and Technische Universität Dresden (Germany). The idea of the project focuses on high-performance telecommunication algorithms and the design and implementation strategies for connecting an FPGA device into a robust and efficient cluster of multi-FPGA systems. The radiation-hardening techniques currently under development are addressing both device and cluster levels, with redundant datapaths on multiple devices, comparing the results and isolating fatal errors. This paper introduces the current state of the project's hardware design description, the composition of the FPGA cluster node, the proposed cluster topology, and the radiation hardening techniques. Intermediate stage experimental results of the FPGA communication layer performance and fault detection techniques are presented. Finally, a wide summary of the project's impact on the scientific community is provided. 1
Proceedings ArticleDOI
03 May 2023
TL;DR: In this paper , single event transient (SET) effects on Tensor Processing Units (TPUs) are investigated and the impact of SETs on the functionality of MMU when executing digital image processing filtering.
Abstract: In recent years, the growth of interest in adopting deep neural network techniques across various domains led to new architectures for supporting the required computational effort. Tensor Processing Units (TPUs), which are based on a systolic array matrix multiplication unit (MMU), became widely popular thanks to their specific structure suitable for Artificial Intelligence. This work investigates Single Event Transient (SET) effects on TPU’s MMU. The analysis demonstrates the impact of SETs on the functionality of MMU when executing digital image processing filtering. The experimental results identify the static and dynamic SET sensitivity of TPU and depict meaningful information on the data dependency of the filters’ kernel values.

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