Choose the most suited hardware for your application leading to conception costs gains, with an average area saving between 20-40% for varied image processing applications.
Optimize the energy consumption of your application. For instance, for the well-known Fast Fourier Transform signal processing benchmark, a reduction of total dynamic on-chip power of 72.5% has been obtained on an Ultrascale +.
61 % of the embedded projects have finished late or have even been cancelled (Source: EE Times Embedded Market's Study 2019). Reduce your time-to-market with our automated optimization tool leading to production costs gains.
With the latest innovative research from reference labs such as IETR and Inria, Quintech proposes its first tool to help embedded systems engineers to reduce their time to market while optimizing their applications. So as to be able to embed millions of code lines in embedded systems, optimization becomes a must-have. So as to get an interesting trade-off between application cost and performance, we propose optimizing the data word-lengths of your application.
After obtaining an electrical engineering degree and a signal processing PhD from INSA Rennes (France), Justine decided to take her research in approximate computing out of the lab with the creation of Kaktus, our MVP. She has led the Quintech project since 2019 and is convinced that it can make embedded software significantly more efficient.
Alexandre is a multidisciplinary engineering manager with over 15 years’ experience in the development, industrialization, and sale of intelligent technological products. On behalf of multinational corporations and deeptech startups, he has successfully brought products to market in the robotics, aerospace, energy, and aviation industries. After leading projects and teams in the Americas, Asia, and Europe, he joined Quintech to quickly commercialize our eco-friendly offer by ensuring the satisfaction of our customer’s needs and expectations. Alexandre holds a B.Sc. in Mechatronics Engineering from the University of Pennsylvania (USA), a M.Sc. in Aerospace Systems Engineering from the Georgia Institute of Technology (USA), and a MBA in Entrepreneurhip from HEC Paris (France).
Pour économiser la batterie, les applications embarquées doivent consommer le minimum d'énergie et fonctionner avec une faible empreinte mémoire. D'où la nécessité d'optimiser le code afin d'alléger le travail du processeur. Dans ce domaine, des résultats de recherche d'Inria et de l'IETR vont aboutir à la création d'une startup autour d'un compilateur facilitant l'identification du meilleur compromis qualité/performance.
Emergences, 2019Read More
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