Solido Launches Machine Learning (ML) Characterization Suite
Suite Accelerates Standard Cell, Memory, and I/O Library Characterization
San Jose, CA – April 6, 2017 – Solido 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.
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