Mentor Sets an ‘Industry Record’ with Calibre Physical Verification

Mentor, a Siemens business, announces that their Calibre physical verification suite has achieved a new standard for electronic design automation software scalability on the Microsoft Azure cloud during scaling experiments on 5nm test chips and a full reticle-sized 7nm production design.

Mentor reports that the Calibre physical verification suite deployments were able to scale out to over 4,000 CPUs, “an industry record for an EDA tool scaling a single job on Azure,” the company says.

Mentor and Azure plan to conduct additional experiments to demonstrate further software scalability and establish recommended chip design sizes to help mutual customers achieve target runtimes in cloud deployments.

Related: The Nearly-Mythical Ice Lake Chip: What Is This New Intel Processor and Why Did It Take So Long?

“Mentor is pleased to have partnered with Microsoft Azure to define a new benchmark with Calibre for scaling for Semiconductor Design Workloads,” said Michael Buehler-Garcia, vice president of product management, Calibre Design Solutions for Mentor.

“As IC companies increasingly look to leverage cloud capacity for faster turnaround times on advanced process node designs, they can be confident that their designs will optimally scale in Microsoft Azure’s robust, secure cloud environment.”

A ‘New Benchmark’ in Software Scalability

“Calibre has set a new benchmark for EDA tool performance, scalability and efficient memory use – all metrics of increasingly critical importance as new semiconductor process nodes introduce unparalleled complexity and encourage ever-larger CPU runs,” said Mujtaba Hamid, head of Product Management, Silicon, Electronics and Gaming, Azure Engineering, Microsoft Corp.

“Calibre supports the rapidly evolving requirements of our semiconductor customers, while demonstrating the outstanding security and performance that Microsoft Azure cloud offers to the demanding EDA market.”

IC designers can use Calibre in any design flow, and while running on either traditional in-house compute configurations or in public cloud environments such as Microsoft Azure, the company says.

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