TOPOLINANO & MAGCAD: A DESIGN AND SIMULATION FRAMEWORK FOR THE EXPLORATION OF EMERGING TECHNOLOGIES

We developed a design framework that enables the exploration and analysis of emerging beyond-CMOS technologies. It is composed of two powerful tools: ToPoliNano and MagCAD. Different technologies are supported, and new ones could be added thanks to their modular structure. ToPoliNano starts from a VHDL description of a circuit and performs the place&route following the technological constraints. The resulting circuit can be simulated both at logical or physical level. MagCAD is a layout editor where the user can design custom circuits, by plac-ing basic elements of the selected technology. The tool can extract a VHDL netlist based on compact models of placed elements derived from experiments or physical simulations. Circuits can be verified with standard VHDL simulators. The design workflow will be demonstrated at the U-booth to show how those tools could be a valuable help in the studying and development of emerging technologies and to obtain feedbacks from the scientific community

FUNCODE: Effective Device-to-System Analysis of Field Coupled Nanocomputing Circuit Designs

Many beyond-CMOS technologies, based on different switching mechanisms, are arising. Field-coupled technologies are the most promising as they can guarantee an extremely low-power consumption and combine logic and memory into the same device. However, circuit-level explorations, like layout verification and analysis of the circuit performance, considering the constraints of the target technology, cannot be done using existing tools. Here, we propose a methodology to take on this challenge. We present FUNCODE (FUNction & COnnection DEtection), an algorithm that can detect element connections, functions and errors of custom-layouts and generate its corresponding VHDL netlist. It is proposed for in-plane and perpendicular Nano Magnetic Logic as a case study. FUNCODE netlists, which take into account the physical behavior of the technology, were verified using circuits with increasing complexity, from 6 up to 1400 gates with a number of layout elements varying from 200 to 2.3e6

On the impact of the stem electrical impedance in neural network algorithms for plant monitoring applications

Smart agriculture offers an environmental-friendly path with respect to unsustainable farming that depletes the nutrients in the soil leading to a persistent degradation of ecosystems caused by population growth. Artificial Intelligence (AI) can help mitigate this issue by predicting plant health status to reduce the use of chemicals and optimize water usage. This paper proposes a custom framework to train neural networks and a comparison among different models to point out the impact and the importance of the stem electrical impedance in addition to environmental parameters for plant monitoring applications. In particular, the paper demonstrates how stem electrical impedance improves the accuracy of the proposed neural network application for plant status classification. The data set is composed of electrical impedance spectra and environmental data acquired on four tobacco plants for a two-month-long experiment. In this paper, we describe the acquisition system architecture, the feature composition of the data set, a general overview of the developed framework, and the training of the neural networks showing the different results considering both the stem impedance and the environmental parameters

ToPoliNano and fiction: Design Tools for Field-coupled Nanocomputing

Field-coupled Nanocomputing (FCN) is a computing concept with several promising post-CMOS candidate implementations that offer tremendously low power dissipation and highest processing performance at the same time. Two of the manifold physical implementations are Quantum-dot Cellular Automata (QCA) and Nanomagnet Logic (NML). Both inherently come with domain-specific properties and design constraints that render established conventional design algorithms inapplicable. Accordingly, dedicated design tools for those technologies are required. This paper provides an overview of two leading examples of such tools, namely fiction and ToPoliNano. Both tools provide effective methods that cover aspects such as placement, routing, clocking, design rule checking, verification, and logical as well as physical simulation. By this, both freely available tools provide platforms for future research in the FCN domain

Long-Range Low-Power Soil Water Content Monitoring System for Precision Agriculture

World population growth and desertification are increasing the food demand. Food production must increase to ensure food security in the following years. Smart agriculture tries to improve food production thanks to the adoption of electronic sensors to monitor and control fruit and vegetable crops. Another critical point in agriculture is the use of potable water. Precision irrigation strategies can be implemented to reduce water waste and increase crop production. This paper proposes a long-range, low-power sensor node to monitor soil water content. It is possible to place multiple sensor nodes in the field and use the gathered data to determine the most suitable irrigation strategy. The node communicates thanks to the LoRa protocol and it can also be used in remote areas where it is impossible to have an internet connection

Analysis of in Vivo Plant Stem Impedance Variations in Relation with External Conditions Daily Cycle

World population growth and desertification are the most severe issue to agricultural food production. Smart agriculture is a promising solution to ensure food security. The use of sensors to monitor crop production can help farmers improve the yield and reduce water consumption. Here we propose a study where the electrical impedance of green plants' stem is analyzed in vivo, along with environmental conditions. In particular, the variations associated with the daily cycle are highlighted. These analyses lead to the possibility of understanding plant status directly from stem impedance