Intento Design was founded in Spring 2015 to provide responsive technology for analog IP. The company was born from 25 years of research aimed at developing a new analog design methodology at Laboratoire d’Informatique de Paris 6 (LIP6) at Université Pierre et Marie Curie (UPMC) in Paris, France. The research resulted in an extensive portfolio of intellectual property, including an innovative EDA tool that accelerates the design cycle by automating the sizing and migration of analog and mixed-signal circuitry used in complex SoCs for a variety of connected applications.
- Consumer: Smartphones, tablets, digital cameras, wearables
- Internet of Things (IoT): Automotive, home automation, industrial
- Big Data: Cloud infrastructure, Access points, routers
- Military: Defense, aerospace
- Medical: Implantable devices, monitoring, dosing
Making these applications a reality means higher integration of analog and mixed-signal circuitry, while achieving the perfect balance of performance, low power consumption, portability and ruggedness. As companies strive to meet these expectations, many design teams are running up against a productivity gap, putting them at risk of missing shrinking time to market windows.
Solving the Productivity Gap
The Intento Design methodology solves the productivity gap inherent in the analog design process by reducing lengthy simulation iterations. Traditionally, analog and mixed-signal design requires the engineer to compute initial circuit dimensions from hand analysis using first order transistor models followed by successive simulations. This tedious and time-consuming process can take weeks for a complex circuit. Intento accelerates this process with software that plugs into the existing design flows and standard tools, and automates the circuit sizing, thereby allowing designers to move on to layout, placement and routing in a fraction of the time.
The Intento Design methodology keeps the designer at the center of the process, specifying the parameters that must be met by the circuit; reviewing the options based on desired power consumption, performance and surface area; and selecting the optimal solution.