industry news
Subscribe Now

Cadence Delivers Machine Learning-Optimized Xcelium Logic Simulation with up to 5X Faster Regressions

Core engine performance enhancements accelerate verification throughput by reducing simulation cycles with matching coverage on randomized test suites

SAN JOSE, Calif., August 12, 2020—Cadence Design Systems, Inc. (Nasdaq: CDNS) today announced the Cadence® Xcelium™ Logic Simulator has been enhanced with machine learning technology (ML), called Xcelium ML, to increase verification throughput. Using new machine learning technology and core computational software, Xcelium ML enables up to 5X faster verification closure on randomized regressions.

Using computational software and a proprietary machine learning technology that directly interfaces to the simulation kernel, Xcelium ML learns iteratively over an entire simulation regression. It analyzes patterns hidden in the verification environment and guides the Xcelium randomization kernel on subsequent regression runs to achieve matching coverage with reduced simulation cycles.

Cadence’s Xcelium Logic Simulator provides best-in-class core engine performance for SystemVerilog, VHDL, mixed-signal, low power, and x-propagation. It supports both single-core and multi-core simulation, incremental and parallel build, and save/restart with dynamic test reload. The Xcelium Logic Simulator has been deployed by a majority of top semiconductor companies, and a majority of top companies in the hyperscale, automotive and consumer electronics segments.

“Kioxia has effectively utilized Xcelium simulation for a variety of our designs, and it addresses our ever-growing verification needs,” said Kazunari Horikawa, senior manager, Design Technology Innovation Division at Kioxia Corporation. “With the new Xcelium ML, we’ve seen a 4X shorter turnaround time in our fully random regression runs to reach 99% function coverage of original, and plan to use this technology in production designs to shorten the time to market for Kioxia’s business.”

“Xcelium ML is a powerful technology and a great example of the significant opportunity we have to leverage machine learning in verification,” said Paul Cunningham, corporate vice president and general manager of the System & Verification Group at Cadence. “Logic simulation continues to be the workhorse of digital verification, and we are investing heavily in fundamental performance optimizations like Xcelium ML to deliver the highest verification throughput to customers using our flow.”

Xcelium ML is part of the Cadence Verification Suite and supports the company’s Intelligent System Design strategy, enabling pervasive intelligence and faster design closure. For more information on Xcelium ML, please visit http://www.cadence.com/go/XceliumML.

About Cadence
Cadence is a pivotal leader in electronic 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 systems for the most dynamic market applications including consumer, hyperscale computing, 5G communications, automotive, aerospace, industrial and healthcare. For six years in a row, Fortune magazine has named Cadence one of the 100 Best Companies to Work For. Learn more at cadence.com.

Leave a Reply

featured blogs
Nov 5, 2024
Learn about Works With Virtual, the premiere IoT developer event. Specifically for IoT developers, Silicon Labs will help you to accelerate IoT development. ...
Nov 13, 2024
Implementing the classic 'hand coming out of bowl' when you can see there's no one under the table is very tempting'¦...

featured video

Introducing FPGAi – Innovations Unlocked by AI-enabled FPGAs

Sponsored by Intel

Altera Innovators Day presentation by Ilya Ganusov showing the advantages of FPGAs for implementing AI-based Systems. See additional videos on AI and other Altera Innovators Day in Altera’s YouTube channel playlists.

Learn more about FPGAs for Artificial Intelligence here

featured paper

Quantized Neural Networks for FPGA Inference

Sponsored by Intel

Implementing a low precision network in FPGA hardware for efficient inferencing provides numerous advantages when it comes to meeting demanding specifications. The increased flexibility allows optimization of throughput, overall power consumption, resource usage, device size, TOPs/watt, and deterministic latency. These are important benefits where scaling and efficiency are inherent requirements of the application.

Click to read more

featured chalk talk

Dependable Power Distribution: Supporting Fail Operational and Highly Available Systems
Sponsored by Infineon
Megatrends in automotive designs have heavily influenced the requirements needed for vehicle architectures and power distribution systems. In this episode of Chalk Talk, Amelia Dalton and Robert Pizuti from Infineon investigate the trends and new use cases required for dependable power systems and how Infineon is advancing innovation in automotive designs with their EiceDRIVER and PROFET devices.
Dec 7, 2023
57,356 views