Pattern matching (PM) was first introduced as the semiconductor industry began to shift from simple one-dimensional rule checks to the two-dimensional checks required by sub-resolution lithography.

Pattern matching is best known for its use in detecting lithographic hotspots, but it’s also widely used across all physical verification flows, and has expanded into design-for-manufacturing (DFM) ...

Among the most elementary examples of machine learning is the one Google provides on identifying iris flowers via its Tensorflow machine learning framework. Artificial intelligence (AI) practitioners ...

As design nodes drop below 45nm, design rules are exploding in number and complexity, making design rule checking (DRC) harder and lengthier. What we have observed across the industry is that the ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...

How often have you struggled to verify static random-access memory (SRAM) blocks in your design? And how often, no matter how much time you spend on them, do they end up causing manufacturing issues?

Learn how to use pattern-matching features in your Java programs, including pattern matching with switch statements, when clauses, sealed classes, and a preview of primitive type pattern matching in ...