Cadence Delivers Machine Learning-Optimized Xcelium Logic Simulation With up to 5X Faster Regressions
August 12 2020 - 12:00PM
Business Wire
Core engine performance enhancements accelerate
verification throughput by reducing simulation cycles with matching
coverage on randomized test suites
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.
© 2020 Cadence Design Systems, Inc. All rights reserved
worldwide. Cadence, the Cadence logo and the other Cadence marks
found at www.cadence.com/go/trademarks are trademarks or registered
trademarks of Cadence Design Systems, Inc. All other trademarks are
the property of their respective owners.
View source
version on businesswire.com: https://www.businesswire.com/news/home/20200812005107/en/
For more information, please contact: Cadence Newsroom
408-944-7039 newsroom@cadence.com
Cadence Design Systems (NASDAQ:CDNS)
Historical Stock Chart
From Mar 2024 to Apr 2024
Cadence Design Systems (NASDAQ:CDNS)
Historical Stock Chart
From Apr 2023 to Apr 2024