Artificial intelligence (AI) promises to revolutionize people’s lives. Whether it’s autonomous cars or advances in the medical industry, we will all benefit from this revolution. Convolution and recurrent neural networks and machine and deep learning algorithms present the opportunity to enable this electronics revolution and create a new silicon renaissance with advances in software and IP.
Train Your Design
Machine learning inside our tools help designers learn from and improve their next-generation design.
Machine learning techniques built into our design flows provide better productivity for design teams.
Optimized processor and advanced-memory IP enable product differentiation.
We’re already using machine learning techniques to produce better, more predictable outcomes for many tasks in the design flow. Machine learning helps our customers meet their time-to-market requirements, improve their design process and reduce the amount of manual intervention necessary. Our tools now suggest solutions to common problems that might otherwise take design teams weeks or months to evaluate.
We are also pushing the leading edge of machine and deep learning research to improve the design of ICs and verification closure with a vision toward design improvement. The Cadence® machine learning team leverages our libraries of algorithms across platforms and products to ensure our ongoing innovation impacts the full breadth of our design tools and IP solutions.
Designing AI devices challenges the traditional capacity, productivity, and compute requirements we traditionally see in the electronics industry. For example, running computationally complex algorithms on standard processors often does not give the performance or power efficiency necessary for compute- and data-intensive machine learning/AI applications. Cadence is a leader in the advanced memory interfaces required by AI applications in servers. Additionally, our Tensilica® DSPs and processors are optimized for audio, vision and AI at-the-edge processing.