industry news
Subscribe Now

Solido Launches Machine Learning (ML) Characterization Suite

San Jose, CA – April 6, 2017Solido Design Automation, a leading provider of variation-aware design and characterization software, today announced the immediate release of its Machine Learning (ML) Characterization Suite. This new product uses machine learning to significantly reduce standard cell, memory, and I/O characterization time, helping semiconductor designers meet aggressive production schedules.

Growth in quickly advancing semiconductor segments, including high performance computing, automotive, mobile, and Internet of Things (IoT), is driving chip complexity with the need to move to more advanced designs. Standard cell, memory, and I/O characterization is a resource-intensive runtime bottleneck, often with challenges to meet production accuracy requirements.

Solido’s ML Characterization Suite significantly reduces the time and resources required for library characterization, while delivering production-accurate library models. ML Characterization Suite’s machine learning algorithms efficiently and accurately model the characterization space. Real-time cross-validation techniques are then applied to determine model error and fit. Solido’s approach is tuned to work across all Liberty data types, including timing, power, noise, waveform, and statistical data.

The following tools are included in ML Characterization Suite:

  • Predictor instantly and accurately generates new Liberty models at new conditions. It does this by modeling the full Liberty space using sparse data from existing Liberty models at other conditions. This reduces up-front characterization time as well as turnaround to generate Liberty files. Predictor works with all Liberty formats and reduces library characterization time by 30% to 70%.

  • Statistical Characterizer quickly delivers true 3-sigma statistical timing data (LVF/AOCV/POCV) values with Monte Carlo and SPICE accuracy, including non-Gaussian distributions. It adaptively selects simulations to meet accuracy requirements and to minimize runtime for all cells, corners, arcs, and slew-load combinations.

“Solido ML Characterization Suite is already in production use at several customers,” said Amit Gupta, president & CEO of Solido Design Automation.  “Extending Solido’s proprietary machine learning technologies from Variation Designer to ML Characterization Suite has already begun delivering disruptive runtime, resource and productivity benefits to our customers.”

Availability

ML Characterization Suite Predictor and Statistical Characterizer products are available immediately.

In other news today, Solido announced launch of its Machine Learning (ML) Labs.

About Solido Design Automation

Solido Design Automation Inc. is a leading provider of variation-aware design and characterization software to technology companies worldwide, improving design performance, power, area and yield.  Solido’s products are currently used in production by more than 1000 designers at over 35 major companies. Solido ML Labs makes Solido’s machine learning technologies and expertise available to semiconductor companies in developing new software products.  The privately held company is venture capital funded and has offices in the USA, Canada, Asia and Europe. For further information, visit www.solidodesign.com or call 306-382-4100.


14 thoughts on “Solido Launches Machine Learning (ML) Characterization Suite”

  1. Pingback: Judi Bola 88
  2. Pingback: Boliden
  3. Pingback: bet535 casino
  4. Pingback: insulation
  5. Pingback: Cheap

Leave a Reply

featured blogs
Apr 23, 2024
The automotive industry's transformation from a primarily mechanical domain to a highly technological one is remarkable. Once considered mere vehicles, cars are now advanced computers on wheels, embodying the shift from roaring engines to the quiet hum of processors due ...
Apr 22, 2024
Learn what gate-all-around (GAA) transistors are, explore the switch from fin field-effect transistors (FinFETs), and see the impact on SoC design & EDA tools.The post What You Need to Know About Gate-All-Around Designs appeared first on Chip Design....
Apr 18, 2024
Are you ready for a revolution in robotic technology (as opposed to a robotic revolution, of course)?...

featured video

How MediaTek Optimizes SI Design with Cadence Optimality Explorer and Clarity 3D Solver

Sponsored by Cadence Design Systems

In the era of 5G/6G communication, signal integrity (SI) design considerations are important in high-speed interface design. MediaTek’s design process usually relies on human intuition, but with Cadence’s Optimality Intelligent System Explorer and Clarity 3D Solver, they’ve increased design productivity by 75X. The Optimality Explorer’s AI technology not only improves productivity, but also provides helpful insights and answers.

Learn how MediaTek uses Cadence tools in SI design

featured chalk talk

Advancements in Motor Efficiency Enables More Sustainable Manufacturing
Climate change is encouraging the acceleration of sustainable and renewable manufacturing processes and practices and one way we can encourage sustainability in manufacturing is with the use of variable speed drive motor control. In this episode of Chalk Talk, Amelia Dalton chats with Maurizio Gavardoni and Naveen Dhull from Analog Devices about the wide ranging benefits of variable speed motors, the role that current feedback plays in variable speed motor control, and how precision measurement solutions for current feedback can lead to higher motor efficiency, energy saving and enhanced sustainability.
Oct 19, 2023
23,863 views