Cadence Design Systems, Inc. announced the delivery of the Cadence® Joint Enterprise Data and AI (JedAI) Platform, enabling a generational shift from single-run, single-engine algorithms in electronic design automation (EDA) to algorithms that leverage big data and AI to optimize multiple runs of multiple engines across an entire SoC design and verification flow. The Cadence JedAI Platform enables engineers to glean actionable intelligence from massive volumes of chip design and verification data, opening the door to a new generation of AI-driven design and verification tools that dramatically improve productivity and power, performance and area (PPA). With the Cadence JedAI Platform, Cadence is unifying big data analytics across its AI platforms—Verisium™ verification, Cadence Cerebrus™ implementation, and Optimality™ system optimization—as well as third-party silicon lifecycle management systems.

With the new Cadence JedAI Platform, engineers can seamlessly manage both structured and unstructured data, including:

• Design data such as waveforms and coverage in functional verification, physical layout shapes, timing/power/voltage/variation analysis reports, design RTL, netlist and SDC specifications in design implementation
• Workload data such as runtime, memory usage and disk space usage, as well as metadata about the inputs to each job and dependencies between them
• Workflow data such as the tools and methodology used to create a design.

The Cadence JedAI Platform makes it easier to manage design complexities associated with emerging consumer, hyperscale computing, 5G communications, automotive and mobile applications and more. Customers using Cadence analog/digital/PCB implementation, verification and analysis software—and even third-party applications—can use the Cadence JedAI Platform to unify and analyze all their big data analytics. Furthermore, the new platform is cloud-enabled, offering highly scalable compute resources in a secure design environment from top cloud providers.

“To enable the semiconductor industry to continue on its strong growth trajectory, it’s critical that the chip design process becomes much more efficient to keep pace with market demands,” said Pat Moorhead, CEO, founder and chief analyst at Moor Insights & Strategy. “Improving design processes through AI and big data analytics creates a clear benefit for engineering teams who can now extract key learnings from the vast quantities of EDA data right at their fingertips. The new Cadence JedAI Platform is designed to provide users with automated, intelligent design insights and the ability to greatly scale engineering team productivity.”

Customers using the Cadence JedAI Platform have access to the following benefits:

• Highly scalable: Enterprise-grade scalability and security, enabling design optimization across multiple runs, tools, users, designs and EDA domains
• Actionable intelligence: Quickly compares metrics across different versions of the same design and/or multiple designs, providing recommended actions to improve PPA and increase verification coverage
• Workflow management technology: Integrated workflow management capability allows users to efficiently capture chip design methodologies and automatically transfer design data between projects through data connectors
• Customized analytics: Offers open industry-standard user interfaces such as Python, Jupyter Notebook and REST APIs, enabling designers to create custom analytics applications.

“Meeting design targets requires a variety of analytics and significant design resources,” said Satoshi Shibatani, director, Digital Design Technology Department, Shared R&D EDA Division, Renesas. “By using the Cadence JedAI Platform’s big data analytics, we can retrieve necessary information and solve bottleneck issues quickly. We’re continuing to expand our AI collaboration with Cadence and use our extensive data effectively to our advantage to improve PPA as well as productivity across all stages of design and verification.”

“As chip design size and complexity has increased exponentially over the past decade, the volume of design and verification data has also increased with it,” said Dr. Venkat Thanvantri, VP of AI R&D at Cadence. “Previously, we saw that once a chip design project was completed, the valuable data was deleted to make way for the next project. There are valuable learnings in the legacy data, and the Cadence JedAI Platform makes it easy for engineering teams to access these learnings and apply them to future designs to deliver optimal engineering productivity and PPA and ultimately more predictable, higher quality product outcomes.”

The Cadence JedAI Platform supports the company’s Intelligent System Design™ strategy, which enables pervasive intelligence for design excellence.