MathWorks and Cadence Solutions

The MathWorks and Cadence integration simplifies the exchange of data, boosts analytics capabilities, and shortens PCB design cycles. The collaboration of two key IC and PCB design solutions to the world’s leading MathWorks modeling tool allows you to focus on your full system design using a unique design flow from system through chip implementation and verification.

IC Design

The integration between the Cadence^® Virtuoso^® ADE Product Suite and MathWorks MATLAB enables you to accelerate processing of large data sets when verifying custom, RF, and mixed-signal designs. With this integration, you can:

• Take advantage of existing MATLAB scripts and seamlessly share data between the Virtuoso and MATLAB platforms, allowing for data mining and efficient analysis in either platform, improving your time to market.
• Utilize MATLAB’s toolboxes and language to easily create and solve complex data calculations that would have previously taken hours to solve using expert coding knowledge and low-level APIs. This data analysis can be performed in either tool, or split between the two, allowing you to pick the most efficient manner to get the calculations and answers.
• Co-simulate system-level models with your mixed-signal designs and testbenches using the power of Simulink integrated with the Spectre^® AMS Designer, which provides a complete mixed-signal verification methodology

PCB Design

Seamlessly integrating proven Cadence PSpice^® technology with industry-leading MATLAB and Simulink products from MathWorks, the PSpice SLPS interface allows co-simulation of electrical and mechanical systems, making it easier to detect critical issues early in the design cycle. When combined with the stress analysis capabilities of the new PSpice Smoke analysis option, the reliability of designs can be analyzed and improved earlier in the design cycle.

Now you can simulate the entire system-level design within the integrated debug environment resulting in a faster, less error-prone process. This is critical for:

• IoT designs where you want to quickly assemble a board and get to market faster
• Automotive designs where reliability, productivity, cost, and manufacturing yield are important