Phải làm gì với tất cả dữ liệu đó – Phân tích dựa trên AI có thể giúp ích
Today’s advanced node chip designs are faced with many new complexities from design and verification down to manufacturing. The solutions used at every stage of chip development generate petabytes of data. Managing, analyzing, understanding, and acting upon that data is overwhelming and paralyzing. Manual interpretation of that data is nearly impossible and at best leads to surface level analysis.
AI has the unique ability to sift through the vast amount of data to identify anomalies and patterns and produce actionable insights that can have significant impact on productivity, design quality and lifecycle, and manufacturing.
Synopsys is hosting our Synopsys.ai Data Analytics Webcast Series to dive deeper into how AI can be used to unlock, connect, and analyze the immensity of data to maximize efficiencies and quality across the full design-to-silicon lifecycle.
The webcast series is segmented into three parts: AI-driven Silicon Analytics, AI-driven Design Analytics, and AI-driven Manufacturing/Fab Analytics.
Integrated SLM Analytics from Design Through Manufacturing
The first presentation in the series takes a look at leveraging design, test, and manufacturing data by automatically highlighting silicon data outliers for improved chip quality, yield, and throughput with Synopsys Silicon.da. It is the first integrated SLM analytics solution that addresses post-silicon challenges by increasing engineering productivity, improving silicon efficiency and providing the tool scalability needed for today’s advanced SoC’s. Silicon.da serves a critical role as part of an overall SLM solution dedicated to improving the health and operational metrics of a silicon device across its complete lifecycle.
In this presentation, Mr. Anti Tseng, Senior Manager at MediaTek, will explain how Silicon.da’s volume diagnostics feature identified systematic issues more efficiently than traditional methods by providing very accurate failure locations within the silicon resulting in improved yield by a single digit percentage and in a shorter amount of time – from weeks to days. Mr. Tseng will also further discuss how utilizing this volume diagnosis analysis technology improves the foundry process for advanced nodes resulting in millions of dollars of cost savings through high volume chip production for fabless companies.
Maximize Productivity with Deep Insights into PPA Trajectories
The second presentation in the series targets design engineers and shows them how to uncover actionable design insights that accelerate the design process with Synopsys Design.da., the industry’s first comprehensive data-visibility and analytic-driven design optimization and signoff closure solution.
The webcast will show how to leverage vast datasets to bring unmatched productivity and a better, faster, and smarter way to design. Techniques will be highlighted on how to siphon metrics data while curating associate analysis data efficiently and automatically to pinpoint areas of focus in real-time and perform analysis to identify PPA bottlenecks and the root-cause. The solution automatically classifies design trends, identifies limitations, and provides prescriptive guided root-cause analysis across the entire design flow.
Comprehensive AI-Driven Process Analytics for Faster Ramp and Efficient High-Volume Manufacturing
The third presentation takes a deeper dive into analyzing data collected throughout the manufacturing process to improve fab yield and throughput, enabling a faster ramp and more efficient high-volume manufacturing (HVM) by utilizing Synopsys Fab.da.
The challenges before semiconductor fabs are expansive and evolving. As the size of chips shrinks from nanometers to eventually angstroms, the complexity of the manufacturing process increases in response. To combat the complexity and sheer intricacy of semiconductor manufacturing, innovative software solutions are required. Synopsys Fab.da is a comprehensive process control solution that utilizes artificial intelligence (AI) and machine learning (ML) to allow for faster production ramp and efficient high-volume manufacturing. Fab.da is a part of the Synopsys.da Data Analytics solutions, which brings together data analytics and insights from the entire chip lifecycle. It can analyze many petabytes of data originating from thousands of equipment in semiconductor fabs with zero downtime.
Learn how the power of AI can help drive your data analytics. Register for these webcasts today.
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