Chip design software firm Synopsys has unveiled Synopsys.ai Copilot as an AI-driven accelerator for designing semiconductor chips.
Sunnyvale, California-based Synopsys said the electronic design automation (EDA) tools uses groundbreaking generative artificial intelligence (GenAI) capability for the copilot. This innovation, born out of a strategic collaboration with Microsoft, leverages the Azure OpenAI Service to infuse the power of GenAI into the intricate field of semiconductor chip design.
The semiconductor industry faces dual challenges of developing faster and more efficient computing while grappling with projected workforce gaps for chip design engineers. Synopsys.ai Copilot aims to address these challenges by introducing conversational intelligence, a generative capability that enhances the chip design process.
Strategic collaboration with Microsoft: Synopsys and Microsoft collaborated to integrate the Azure OpenAI Service, providing access to OpenAI’s large language models (LLMs) within the robust capabilities of Microsoft Azure. This integration lays the foundation for Synopsys.ai Copilot, an AI-driven breakthrough in chip design.
AI-driven design for semiconductor innovation: Synopsys, known for pioneering AI-driven electronic design automation with Synopsys.ai EDA suite, is taking a step further with Synopsys.ai Copilot. This generative capability, fueled by Azure OpenAI Service, offers conversational intelligence, addressing the growing complexity in semiconductor engineering.
Addressing workforce gap with AI: Shankar Krishnamoorthy, general manager of the Synopsys EDA Group, highlighted in a statement the workforce challenges, saying, “AI-driven design can help address these challenges.” With a projected 15% to 30% workforce gap for chip design engineers by 2030, AI becomes a crucial ally in accelerating design processes.
AI-powered experiences: Synopsys.ai Copilot is designed to work alongside designers in their everyday tools, enabling conversational intelligence in natural language across the design team. It’s the first in a series of planned generative AI capabilities from Synopsys, poised to learn new skills and adapt to teams’ evolving needs, the company said.
Infrastructure at scale: Deployable in any on-premises or cloud environment, Synopsys.ai Copilot integrates Microsoft Azure’s high-performance computing infrastructure. This ensures the availability, affordability, and capacity required to handle AI workloads for advanced chip design and verification applications, Synopsys said.
Safe and responsible design: The collaboration between Synopsys and Microsoft emphasizes building responsible AI systems that are safe and trustworthy. This commitment aims to promote the secure deployment of AI technologies in creating new silicon-based applications, the companies said.
Synopsys.ai Copilot is already available for early-access customers, offering AI-powered experiences and infrastructure at scale. The combination of AI-driven design capabilities and high-performance infrastructure is anticipated to significantly improve innovation efficiency for engineering teams.
Chip design software firm Synopsys has unveiled Synopsys.ai Copilot as an AI-driven accelerator for designing semiconductor chips.
Sunnyvale, California-based Synopsys said the electronic design automation (EDA) tools uses groundbreaking generative artificial intelligence (GenAI) capability for the copilot. This innovation, born out of a strategic collaboration with Microsoft, leverages the Azure OpenAI Service to infuse the power of GenAI into the intricate field of semiconductor chip design.
The semiconductor industry faces dual challenges of developing faster and more efficient computing while grappling with projected workforce gaps for chip design engineers. Synopsys.ai Copilot aims to address these challenges by introducing conversational intelligence, a generative capability that enhances the chip design process.
Design highlights
Strategic collaboration with Microsoft: Synopsys and Microsoft collaborated to integrate the Azure OpenAI Service, providing access to OpenAI’s large language models (LLMs) within the robust capabilities of Microsoft Azure. This integration lays the foundation for Synopsys.ai Copilot, an AI-driven breakthrough in chip design.
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AI-driven design for semiconductor innovation: Synopsys, known for pioneering AI-driven electronic design automation with Synopsys.ai EDA suite, is taking a step further with Synopsys.ai Copilot. This generative capability, fueled by Azure OpenAI Service, offers conversational intelligence, addressing the growing complexity in semiconductor engineering.
Addressing workforce gap with AI: Shankar Krishnamoorthy, general manager of the Synopsys EDA Group, highlighted in a statement the workforce challenges, saying, “AI-driven design can help address these challenges.” With a projected 15% to 30% workforce gap for chip design engineers by 2030, AI becomes a crucial ally in accelerating design processes.
AI-powered experiences: Synopsys.ai Copilot is designed to work alongside designers in their everyday tools, enabling conversational intelligence in natural language across the design team. It’s the first in a series of planned generative AI capabilities from Synopsys, poised to learn new skills and adapt to teams’ evolving needs, the company said.
Infrastructure at scale: Deployable in any on-premises or cloud environment, Synopsys.ai Copilot integrates Microsoft Azure’s high-performance computing infrastructure. This ensures the availability, affordability, and capacity required to handle AI workloads for advanced chip design and verification applications, Synopsys said.
Safe and responsible design: The collaboration between Synopsys and Microsoft emphasizes building responsible AI systems that are safe and trustworthy. This commitment aims to promote the secure deployment of AI technologies in creating new silicon-based applications, the companies said.
Early access
Synopsys.ai Copilot is already available for early-access customers, offering AI-powered experiences and infrastructure at scale. The combination of AI-driven design capabilities and high-performance infrastructure is anticipated to significantly improve innovation efficiency for engineering teams.
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Author: Dean Takahashi
Source: Venturebeat
Reviewed By: Editorial Team
