- Industry’s first generative AI-driven technology to predict, root cause and resolve IR drop issues early in the design process
- New breakthrough technology uses machine learning-generated power grid models to enable fast IR inferencing within design implementation
- Improves PPA by eliminating the need to overdesign the power grid due to early IR drop prediction and prevention capabilities
- Voltus InsightAI seamlessly integrates with the Cadence digital full flow and system design and analysis platform for efficient EM-IR-driven design closure
Cadence Design Systems, Inc. (Nasdaq: CDNS) today announced the new Cadence® Voltus™ InsightAI, the industry’s first generative AI technology that automatically identifies the root cause of EM-IR drop violations early in the design process and selects and implements the most efficient fixes to improve power, performance, and area (PPA). Using Voltus InsightAI, customers can fix up to 95% of violations prior to signoff, leading to a 2X productivity improvement in EM-IR closure.
Power integrity is a major design challenge at advanced nodes, with designers regularly facing a significant number of EM-IR violations at signoff, making it imperative to address this challenge early in the design phase. One of the major bottlenecks of in-design EM-IR analysis is that it is computationally very expensive due to the size and coupled nature of the power network. The new AI-driven Voltus InsightAI helps to overcome this bottleneck by utilizing new breakthrough machine learning methods for very fast incremental IR analysis. Using Voltus InsightAI, customers can use in-design analysis to enhance on-chip and chiplet power integrity. The technology enables greater engineering efficiency for uncovering issues early and offers key productivity-enhancing features:
- Fast IR Inferencing Engine: The solution uses proprietary neural networks to build models of the power grid and can perform extremely fast incremental IR analysis to provide instant feedback on the impact of design changes.
- IR Drop Diagnostics: Voltus InsightAI uses deep learning to discover the root cause of IR drop problems and can quickly identify aggressors, victims and resistance bottlenecks. It uses electrical, spatial and timing factors for predicting IR drop issues during design.
- Multi-Method Fixing: Decision-tree methods are utilized to perform timing and design rule check (DRC)-aware fixes of IR drop, using multiple methods like placement, grid reinforcement, routing and engineering change orders (ECOs). Voltus InsightAI selects precise fixing methods based on the root cause of the problem, driving better utilization and improved PPA.
- Fully Integrated Solution: Voltus InsightAI is fully integrated with Cadence’s solutions, including the Cadence Innovus™ Implementation System, the Cadence Tempus™ Timing Solution, the Cadence Voltus IC Power Integrity Solution, and the Cadence Pegasus™ Verification System for complete IR design closure from implementation to signoff that is timing- and DRC-aware.
“As we move to more advanced nodes, EM-IR is quickly becoming one of the most pressing challenges, requiring novel and innovative approaches to address customer needs. With Voltus InsightAI, Cadence has pioneered applying generative AI technology to EM-IR, focusing not just on signoff, but early detection and prevention of EM-IR violations as well,” said Ben Gu, Corporate Vice President of R&D, Multiphysics Systems Analysis Business Unit, Cadence. “With this capability, designers don’t need to over-design the power grid, thereby enabling far better PPA. Customers are seeing impressive results as they can leverage this breakthrough technology to fix up to 95% of violations prior to signoff and achieve more than 2X productivity improvement in EM-IR closure.”
The generative AI-driven Voltus InsightAI supports Cadence’s Intelligent System Design™ strategy, enabling SoC design excellence. Customers can learn more at www.cadence.com/go/VoltusInsightAI.
“As the provider of foundational technology, reducing complexities of power integrity on advanced nodes is critical in ensuring we can continue to meet performance requirements of the next era of computing. said. We are enthusiastic about the initial results of our evaluation of the Cadence Voltus InsightAI technology on a 3nm Arm Cortex-X4 core block and we look forward to continuing our work with Cadence on this technology to help close the power integrity gap on advanced nodes.”
- Berkan Baran, vice president of implementation, Solutions Engineering Group, Arm
“We have evaluated the new Cadence Voltus InsightAI and see promise in the technology to fix IR drop violations. The tool was automatically able to fix a significant number of violations in a very efficient manner. We are working with Cadence to deploy it for future projects.”
- Jon Stahl, Senior Director of ASIC Development, Cisco (Acacia)
“As one of the world’s leading semiconductor companies, MediaTek must push the boundaries of chip design, and we need highly advanced software solutions to help us achieve our aggressive time-to-market goals. Using the new Cadence Voltus InsightAI technology, we have seen a 65 – 70% reduction in IR drop violations at the block level, and designs were optimized using both vector-based and vectorless flows.”
- CC Mao, Deputy General Manager, Computing and Artificial Intelligence Technology Group, MediaTek
Cadence is a pivotal leader in electronic systems design, building upon more than 30 years of computational software expertise. The company applies its underlying Intelligent System Design strategy to deliver software, hardware and IP that turn design concepts into reality. Cadence customers are the world’s most innovative companies, delivering extraordinary electronic products from chips to boards to complete systems for the most dynamic market applications, including hyperscale computing, 5G communications, automotive, mobile, aerospace, consumer, industrial and healthcare. For nine years in a row, Fortune magazine has named Cadence one of the 100 Best Companies to Work For. Learn more at cadence.com.
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