- Scilab
free/libre and open source software for numerical computation developed by Scilab Enterprises, France. Scilab also includes Xcos which is an open source alternative to Simulink. - Python
general-purpose, high-level, remarkably powerful dynamic programming language that is used in a wide variety of application domains. It supports multiple programming paradigms. - eSim
(formerly known as Oscad/FreeEDA) is an EDA tool for circuit design, simulation, analysis and PCB design. It is developed by the FOSSEE team at IIT Bombay - Osdag
free/libre and open-source software which allows the user to design steel structures using a graphical user interface. The GUI also provides 3D visualization of the designed component and images - DWSIM
free/libre and open source CAPE-OPEN compliant chemical process simulator. Helps understand the behavior of Chemical Systems by using rigorous thermodynamic and unit operations models. - OpenFOAM
free/libre and open source CFD toolbox useful to solve anything from complex fluid flows involving chemical reactions, turbulence and heat transfer, to solid dynamics and electromagnetics. - OpenModelica
free/libre and open source environment based on the Modelica modelling language for modelling, simulating, optimising and analysing complex dynamic systems. - OpenPLC
free/libre and open source Programmable Logic Controller creating opportunities for people to study its concepts, explore new technologies and share the resources. - FLOSS-Arduino
control of Arduino using Free/Libre Open-Source Software. The interface helps the user to perform embedded systems experiments on the Arduino Uno board. - SBHS
(Single Board Heater System) is a lab-in-a-box setup useful for teaching and learning control systems. - R
programing language and environment for statistical computing and graphics. - QGIS
(Quantum GIS) is a free and open-source desktop Geographic Information System (GIS) application. - FOCAL
an initiative by FOSSEE to promote Open Source Software in computer graphics. - SOUL
(Science OpensoUrce Software for Teaching Learning) is a collection of ICT software that can be used as teaching/learning tools by the community of educators and the learners to teach/ learn the basic as well as the advanced concepts in science subjects
Mar 21, 2024
[FOSSEE] Better Education
Mar 20, 2024
[gnugen] Install Fest and Workshop git
Come discover Linux and if you want, we'll be ready to help you install it on your computer !
(remember to take a backup of your data before, just in case)
📌 Where: EPFL CM 1 100
Workshop: just do git, at 13h30 if you'd like to learn how to use git for an efficient collaboration
Mar 19, 2024
[Habilitation] Assessment of novel devices in CMOS technology
IEEE 5NANO2024 Conference 25-26th April, 2024
Nanomaterials, Nanobioscience & Nanotechnology
VISAT Engineering College,
Elanji, Ernakulam, Kerala, India - 686 665
Tel: +91 9447691397, +91 9486881397.
E-mail: deanresearch@visat.ac.in, tdsubash2007@gmail.com, 5nano2k24@gmail.com
Website: https://www.5nano2024.com
Mar 18, 2024
[paper] in-memory computing using FeFET
1 Robert Bosch GmbH, Renningen, Germany
2 Semiconducture Test and Reliability, University of Stuttgart, Stuttgart, Germany
3 Department of Electrical Engineering, IIK, Kanpur, India
4 Fraunhofer IPMS, Dresden, Germany
5 RPTU Kaiserslautern-Landau, Kaiserslautern, Germany
6 MIRMI; Technical University of Munich, Germany
Abstract: Advancements in AI led to the emergence of in-memory-computing architectures as a promising solution for the associated computing and memory challenges. This study introduces a novel in-memory-computing (IMC) crossbar macro utilizing a multi-level ferroelectric field-effect transistor (FeFET) cell for multi-bit multiply and accumulate (MAC) operations. The proposed 1FeFET-1R cell design stores multi-bit information while minimizing device variability effects on accuracy. Experimental validation was performed using 28 nm HKMG technology-based FeFET devices. Unlike traditional resistive memory-based analog computing, our approach leverages the electrical characteristics of stored data within the memory cell to derive MAC operation results encoded in activation time and accumulated current. Remarkably, our design achieves 96.6% accuracy for handwriting recognition and 91.5% accuracy for image classification without extra training. Furthermore, it demonstrates exceptional performance, achieving 885.4 TOPS/W–nearly double that of existing designs. This study represents the first successful implementation of an in-memory macro using a multi-state FeFET cell for complete MAC operations, preserving crossbar density without additional structural overhead.
Acknowledgements: This work has received funding from the ECSEL Joint Undertaking (JU) under grant agreement No 826655 and No 876925. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Belgium, France, Germany, Portugal, Spain, The Netherlands, Switzerland. Open Access funding enabled and organized by Projekt DEAL.