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AI Startups are Using the Cloud to Accelerate Chip Design and Time-to-Market

Synopsys Editorial Staff

Nov 18, 2024 / 4 min read

It¡¯s no surprise that AI technologies ¡ª and the chips that enable them ¡ª are in massive demand. The processor and accelerator market for AI applications is expected to reach , representing more than 263% growth over a five-year span.

What may come as a surprise, however, is the number of new businesses looking to capitalize on this growth. Despite significant barriers to entry, .

Because these new entrants typically don¡¯t have the infrastructure or resources of traditional semiconductor companies, many are using non-traditional approaches to innovate and compete. And much of it comes down to speed.

There¡¯s no better way to level the playing field than beating the competition to market, and many AI chip startups are using cloud-based tools to accelerate their design cycles.

Here are three examples. 

Rain AI develops novel AI accelerator chip from scratch

A Series A company backed by AI pioneers like and , Rain AI set out to develop the world¡¯s most energy efficient AI hardware. Their novel AI accelerator necessitated full System-on-Chip (SoC) architecture exploration (based on real world workloads). It required tight integration between digital, analog, and RISC-V components. And it needed to be designed and developed from scratch.  

¡°Rain AI is on a mission to redefine compute for AI workloads and is designing AI accelerator chips for record balance between speed, power, area, accuracy, and cost,¡± says JD Allegrucci, Head of Hardware Engineering at Rain AI. ¡°Designing these complex architectures requires best-in-class EDA tools and IP.¡±

With a goal of turning concept into hardware within a year, speed and first-pass silicon success were also critical. Rain AI achieved both with the help of Synopsys Cloud, which combines SaaS-based EDA tools and IP with pre-optimized infrastructure from cloud leaders like .

¡°We were able to set up the EDA environment within days and start the architecture exploration ¡ª for AI workloads, design, verification, and backend flow ¡ª within a few weeks,¡± says Nawab Ali, Principal Engineer at Rain AI. ¡°It allowed us to focus on our design rather than setting up and managing the environment.¡±

Fast infrastructure setup and architectural exploration coupled with increased engineering productivity enabled Rain AI to successfully meet their fast-track development goals.

¡°Synopsys Cloud provided unique capabilities to handle iterative and complex design cycles with unlimited license scalability to accelerate our entire project and deliver high-quality results within schedule,¡± Allegrucci says.

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Mentium overcomes infrastructure, licensing, and budget constraints

With a critical development milestone looming, AI startup needed to scale their compute and storage resources and overcome EDA licensing and budget limitations.

¡°We were at risk of missing a tapeout,¡± says Mirko Prezioso, Cofounder and CEO of Mentium, which is developing edge-focused, AI-driven co-processors for space, robotics, and security applications.

Without time or CapEx for more infrastructure and additional licenses, the company turned to Synopsys Cloud and Microsoft Azure.

¡°We were amazed to see the capabilities of Synopsys Cloud,¡± Prezioso says. ¡°We were able to set up the entire CAD/IT environment quickly and scale EDA licenses on a per-minute basis for each job.¡±

Released from the constraints of onsite infrastructure, seat-based licensing, and the upfront spending typically required for both, Mentium was able to stand up a production environment in days and get its design schedule back on track in weeks.

¡°We were able to deliver our first tapeout on time and worked on pulling in the schedule for the next tapeout,¡± Prezioso reports. ¡°With an intuitive UI/UX coupled with on-demand compute, storage, and true pay-per-use access, Synopsys Cloud allows us to harness the full potential of the cloud for EDA workloads to complete designs faster and with improved quality.¡±

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TetraMem aligns global development team and AI chip verification processes

Seeking to develop a novel AI accelerator with cutting-edge in-memory computing (IMC) technology, faced three distinct challenges. First, the accelerator¡¯s complex design required smooth integration and verification of analog in-memory computing and the digital RISC-V processor. Second, the startup¡¯s development team was spread across multiple continents. And third, the company had aggressive time-to-market targets.

EDA tools and preconfigured design flows from Synopsys Cloud and optimized infrastructure from Microsoft Azure helped overcome all three.

¡°We were able to achieve a very fast infrastructure setup on the Synopsys Cloud EDA environment within days,¡± says Wenbo Yin, VP of IC Design at TetraMem. ¡°The vast selection of EDA tools and IP available on the cloud enabled us to start the design, verification, and backend flow very quickly.¡±

In addition to enabling the rapid deployment of a full production environment, the cloud-based solution dramatically improved the collaboration and efficiency of TetraMem¡¯s globally distributed design team.

¡°Synopsys Cloud has played a pivotal role in helping us accomplish our mission by providing seamless access to a highly secure and complete SoC design environment,¡± says Dr. Glenn (Ning) Ge, CEO and Cofounder of TetraMem. ¡°With scalable access to EDA software, preconfigured end-to-end flows, and infrastructure resources, we can tapeout quickly and efficiently.¡±

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