Agile Standards


Semiconductor Engineering sat down with Lu Dai, chairman for Accellera and senior director of engineering at Qualcomm, to discuss what's changing in standards development. What follows are excerpts of that conversation. SE: Accellera has had a great first half of the year. Dai: Yes, we are only half way through the year and yet we got Portable Stimulus Standard (PSS) out, the SystemC CCI ... » read more

Faster Verification With AI, ML


Tool providers have continually improved the performance, capacity, and memory footprint parameters of functional verification engines over the past decade. Today, although the core anchors are still formal verification, simulation, emulation, and FPGA-based prototyping, a new frontier focusing on the verification fabric itself aims to make better use of these engines including planning, alloca... » read more

Why Parallelization Is So Hard


Semiconductor Engineering sat down to talk about parallelization efforts within EDA with Andrea Casotto, chief scientist for Altair; Adam Sherer, product management group director in the System & Verification Group of Cadence; Harry Foster, chief scientist for Mentor, a Siemens Business; Vladislav Palfy, global manager for applications engineering at OneSpin; Vigyan Singhal, chief Oski for ... » read more

When Bugs Escape


Bugs are a fact of life, and they always have been. But verification methodologies may not have evolved fast enough to keep up with the growing size and complexity of systems. The types of bugs are changing, too. Some people call these corner cases. Others call them outliers. Still another group refers to them as simulation-resistance superbugs. In markets such as automotive, the notion o... » read more

Design Verification Is All About Good Hygiene


Design verification has a lot in common with human hygiene practices. The goal of both activities is to remove all dirt, grime, and bugs through an active process of establishing good hygiene. If this process is not followed properly, the result is viruses, infections, and other illnesses. Good verification hygiene is as important in semiconductor development as human hygiene is for a healthy b... » read more

Verification As A Flow


Semiconductor Engineering sat down to discuss the transformation of verification from a tool to a flow with Vladislav Palfy, global manager application engineering for OneSpin Solutions; Dave Kelf, chief marketing officer for Breker Verification Systems; Mark Olen, product marketing group manager for Mentor, A Siemens Business; Larry Melling, product management director, System & Verificati... » read more

Power-Aware Static Checks: Static Checker Results And Debugging Techniques


In Part 1 of this three article series on power aware (PA) verification, we examined the foundations and verification features of PA static checks. In Part 2, we discussed the features of the static verification library and described best static verification practices. Part 3 concludes this series with details of static PA verification tool procedures using a real example to analyze PA-Stati... » read more

Low Power Coverage


Through real design examples and case studies, this paper demonstrates how to achieve comprehensive low power design verification closure with all possible sources of power states, their transition coverage, and cross-coverage of power domains of interdependent states. As well the paper proposes a mechanism to combine and represent LP and non-LP coverage in a unified and adaptable database with... » read more

Verification As A Flow


Semiconductor Engineering sat down to discuss the transformation of verification from a tool to a flow with Vladislav Palfy, global manager application engineering for OneSpin Solutions; Dave Kelf, chief marketing officer for Breker Verification Systems; Mark Olen, product marketing group manager for Mentor, A Siemens Business; Larry Melling, product management director, System & Verificati... » read more

Security Holes In Machine Learning And AI


Machine learning and AI developers are starting to examine the integrity of training data, which in some cases will be used to train millions or even billions of devices. But this is the beginning of what will become a mammoth effort, because today no one is quite sure how that training data can be corrupted, or what to do about it if it is corrupted. Machine learning, deep learning and arti... » read more

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