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Today¡¯s advanced node chip designs are faced with many new complexities which require more verification, more validation and more analysis. The resulting data from these added steps has also grown exponentially and engineers need a way to efficiently analyze this information. The result is a new paradigm shift which has led to data overload requiring tools to collect huge amounts of data from design, test and manufacturing (petabytes), analyze the data, and provide actionable insights on that data.

Part of the Synopsys.da AI analytics tools,  Synopsys¡¯ Silicon.da 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 ¨C 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.