Using AI And Bugs To Find Other Bugs


Debug is starting to be rethought and retooled as chips become more complex and more tightly integrated into packages or other systems, particularly in safety- and mission-critical applications where life expectancy is significantly longer. Today, the predominant bug-finding approaches use the ubiquitous constrained random/coverage driven verification technology, or formal verification techn... » read more

Using Verification Data More Effectively


Verification is producing so much data from complex designs that engineering teams need to decide what to keep, how long to keep it, and what they can learn from that data for future projects. Files range from hundreds of megabytes to hundreds of gigabytes, depending on the type of verification task, but the real value may not be obvious unless AI/machine learning algorithms are applied to a... » read more

I’m Almost Done


The city of Belgrade is renovating the street where I live. They are also building a new building next to mine so that I can see the construction work from my balcony. Last week, they blocked the street for some 20 minutes, and people got out of their cars and waited outside for the road to open. The construction workers were not in a hurry, and it seemed like everyone was ok with that, so I... » read more

Increase LVS Verification Productivity In Early Design Cycles


With the innovative Calibre nmLVS-Recon early verification tool, designers can run targeted short isolation analysis and debugging on blocks, macros and chips in early design phases. The Calibre nmLVS-Recon short isolation use model focuses on fast, efficient, prioritized short isolation and short paths debugging. To read more, click here. » read more

Debugging Debug


While semiconductor verification techniques have evolved considerably over the last 25 years, the debug of design problems found during verification has barely changed. New algorithms including machine learning, visualization approaches, and problem solving ideas allow a different approach to debug that saves up to an order of magnitude in debug time. Vtool has introduced Cogita, a next-generat... » read more

Challenges In Using AI In Verification


Pressure to use AI/ML techniques in design and verification is growing as the amount of data generated from complex chips continues to explode, but how to begin building those capabilities into tools, flows and methodologies isn't always obvious. For starters, there is debate about whether the data needs to be better understood before those techniques are used, or whether it's best to figure... » read more

The Evolution Of Digital Twins


Digital twins are starting to make inroads earlier in the chip design flow, allowing design teams to develop more effective models. But they also are adding new challenges in maintaining those models throughout a chip's lifecycle. Until a couple of years ago, few people in the semiconductor industry had even heard the term "digital twin." Then, suddenly, it was everywhere, causing confusion ... » read more

Multi-Mode Clock Domain Crossing Verification Enables Analysis Efficiency And Accuracy


This paper shows how automated modal CDC analysis is used to exhaustively verify CDC issues in all test and operational modes of an SoC with multiple IPs. This new approach automatically consolidates all results from each mode, making issues very easy to interpret and debug. What took days and weeks with the prior manual approach now takes only a few hours. To read more, click here. » read more

Simplifying And Speeding Up Verification


Semiconductor Engineering sat down to discuss what's ahead for verification with Daniel Schostak, Arm fellow and verification architect; Ty Garibay, vice president of hardware engineering at Mythic; Balachandran Rajendran, CTO at Dell EMC; Saad Godil, director of applied deep learning research at Nvidia; Nasr Ullah, senior director of performance architecture at SiFive. What follows are excerpt... » read more

An Eye For An AI


AI comes in multiple forms and flavors. The challenge is choosing the right one for the right purpose, and recognizing that just because AI can be applied to a particular process or problem doesn't mean it should be. While AI has been billed as a ideal solution for just about every problem, there are three primary requirements for a successful application. First, there needs to be sufficient q... » read more

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