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Artificial intelligence (AI) is making its way into every industry (including the chip design world), and for good reason. AI enables faster processes, improves decision-making, reduces human error, assists with mundane and repetitive tasks, and more. With growing design complexity and shrinking market windows, new approaches in chip design are needed to meet the demand for silicon that can power next-generation data centers, medical tech devices, the latest smartphone models, as well as tackle global issues such as climate change and energy efficiency.
However, given the complexity of the design process, utilization and adoption of AI technologies in the semiconductor industry, specifically in the EDA tools market, was slow in the early days. That¡¯s when Synopsys saw an opportunity to leverage AI and unleash its potential to design chips. The realization led to the Synopsys DSO.ai? solution, the industry¡¯s first AI-driven reinforcement learning chip design technology with proven ability to enable significant productivity and performance gains, along with cloud scalability.
We are just scratching the surface with chip design with AI as there is unlimited potential to expand its use to the entire EDA design flow from architecture to manufacturing. The industry faces challenges such as unprecedented development timeframes, engineering resource constraints, and the growing cost and risk in manufacturing processes ¨C all of which can be improved with the help of AI.
Continue reading to learn more about the benefits and future of AI in chip design as well as Synopsys¡¯ role in this innovative new era.
Main Benefits of AI in Chip Design
From reducing design time to improving performance and providing feedback as early as the architectural design stage, the benefits of AI in chip design are plentiful as AI changes how companies design chips. Among these benefits, the overarching theme is greater productivity and how fast chips can be designed and delivered to the market without sacrificing the quality of results.
Additionally, AI enhances productivity by minimizing costs, requiring fewer resources, and, most importantly, freeing up time for design teams to focus on disruptive innovations. This impact is significant because companies can effectively utilize their talent pool and increase throughput to invest in future market-leading products.
AI allows designers to be more efficient while simultaneously improving design quality in the long run. On the power, performance, and area (PPA) front, AI can catch human errors and find solutions to get the best quality of results, which would otherwise be a challenge for human-only iterations in terms of both speed and accuracy.
AI is offering opportunities to enable self-optimizing design tools. Very much like self-driving cars that observe real-world interactions to improve their responses in different (local) driving conditions, AI-driven tools are able to learn with every design iteration and improve the AI models to effectively scale across blocks and projects for faster time to market.
Applications of Chip Design with AI
From autonomous vehicles to facial recognition, simulation, and 5G for mobile devices, AI is already used in an array of real-life applications, powering popular products that are known to help us in our day-to-day lives.
Some of the first Synopsys DSO.ai customers used the technology to design highly advanced CPUs, DSPs, and GPUs for a variety of end applications. Because the hardware market leaves much room for AI innovation, it also presents a unique set of challenges due to intensive resource requirements to its pioneers, with both cloud and edge segments pushing the limits of existing silicon technologies for PPA.
AI also enables the exploration of different architectures for emerging verticals such as automotive and AI chips, as these verticals have unique requirements. If you¡¯re coming up with a new AI chip architecture, AI can help perform what-if analysis on key considerations such as power network distribution and top-level interconnect planning for the many compute units.
Synopsys Paves the Way Forward for Chip Design in AI
Since the chip development flow encompasses several steps, the more tightly the AI-driven solutions are integrated, the better the outcomes. Using Synopsys AI technology, customers have seen more than 3x productivity increases and up to 20% better quality of results, with reduced use of overall resources. And we¡¯re just getting started.
The era of AI in chip design is here, and Synopsys is helping other design companies reap the benefits as we see AI adoption continue to accelerate exponentially. Synopsys is invested in infusing AI within the semiconductor industry ecosystem and supply chain. As a leader in AI thought leadership and execution, Synopsys is paving the way for the next wave of advanced designs.