Using AI To Close Coverage Gaps

Verification of complex, heterogeneous chips is becoming much more difficult and time-consuming. There are more corner cases, and devices have to last longer and behave according to spec throughout their lifetimes. This is where AI fits in. It can help identify redundancy and provide information about why a particular device or block may not be able to be fully covered, and it can do it in less... » read more

Advanced RISC-V Verification Methodology Projects

The open standard of RISC-V offers developers new freedoms to explore new design flexibilities and enable innovations with optimized processors. As a design moves from concept to implementation new resources are appearing to help with standards for testbenches, verification IP reuse, and coverage analysis. RISC-V offers every SoC team the possibility to design an optimized processor, but this a... » read more

Accelerating Coverage Closure With AI-Based Verification Space Optimization

Coverage is at the heart of all modern semiconductor verification. There is no maxim more fundamental to this process than “if you haven’t exercised it, you haven’t verified it.” Although covering a particular aspect of a chip design does not guarantee that all bugs are found — bug effect propagation and checker quality are also key factors — it is certainly true that bugs cannot po... » read more

How AI Drives Faster Verification Coverage And Debug For First-Time-Right Silicon

By Taruna Reddy and Robert Ruiz These days, the question is less about what AI can do and more about what it can’t do. From talk-of-the-town chatbots like ChatGPT to self-driving cars, AI is becoming pervasive in our everyday lives. Even industries where it was perhaps an unlikely fit, like chip design, are benefiting from greater intelligence. What if one of the most laborious, time-co... » read more

Everything, Everywhere, All At Once: Big Data Reimagines Verification Predictability And Efficiency

Big data is a term that has been around for many years. The list of applications for big data are endless, but the process stays the same: capture, process and analyze. With new, enabling verification solutions, big data technologies can improve your verification process efficiency and predict your next chip sign-off. By providing a big data infrastructure, with state-of-the-art technologies... » read more

A New Year’s Wish

Every year I run a predictions article. It is a mashup of ideas from many people within the industry, and while many predictions are somewhat self-serving, there are other which come more from the heart — or perhaps they are dreams rather than expectations. I see hope in some of those, particularly the ones that look toward sustainability within our industry, and of our industry. Just like... » read more

Improving Concurrent Chip Design, Manufacturing, And Test Flows

Semiconductor design, manufacturing, and test are becoming much more tightly integrated as the chip industry seeks to optimize designs using fewer engineers, setting the stage for greater efficiencies and potentially lower chip costs without just relying on economies of scale. The glue between these various processes is data, and the chip industry is working to weave together various steps t... » read more

New Processor Fuzzing Mechanism

Researchers from Boston University and University of Washington published a technical paper titled "ProcessorFuzz: Guiding Processor Fuzzing using Control and Status Registers." Abstract "As the complexity of modern processors has increased over the years, developing effective verification strategies to identify bugs prior to manufacturing has become critical. Undiscovered micro-architectur... » read more

ML And UVM Share Same Flaws

A number of people must be scratching their heads over what UVM and machine learning (ML) have in common, such that they can be described as having the same flaws. In both cases, it is a flaw of omission in some sense. Let's start with ML, and in particular, object recognition. A decade ago, Alexnet, coupled with GPUs, managed to beat all of the object detection systems that relied on tradit... » read more

Is AI Improving A Broken Process?

Verification is fundamentally comparing two models, each derived independently, to find out if there are any different behaviors expressed between the two models. One of those models represents the intended design, and the other is part of the testbench. In an ideal flow, the design model would be derived from the specification, and each stage of the design process would be adding other deta... » read more

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