Increase In Analog Problems


Analog and mixed signal design has always been tough, but a resent survey suggests that the industry has seen significantly increased failures in the past year because the analog circuitry within an ASIC was out of tolerance. What is causing this spike in failures? Is it just a glitch in the data, or are these problems real? The answer is complicated, and to a large extent it depends heavily... » read more

Machine Learning Enabled High-Sigma Verification Of Memory Designs


Emerging applications and the big data explosion have made memory IPs ubiquitous in modern-day electronics. Specifically, the demand for memories with low-die area, low voltage, high capacity, and high performance is rising for use by data center and cloud computing servers. This is essential to serve the exponentially growing connectivity boom and the latest emerging 5G based systems, includin... » read more

Confusion Grows Over Packaging And Scaling


The push toward both multi-chip packaging and continued scaling of digital logic is creating confusion about how to classify designs, what design tools work best, and how to best improve productivity and meet design objectives. While the goals of design teams remains the same — better performance, lower power, lower cost — the choices often involve tradeoffs between design budgets and ho... » read more

SystemVerilog Constraints


This paper looks at two of the most common issues when constraint solver results do not match your intent: Not understanding how Verilog expression evaluation rules apply to interpret the rules of basic algebra and not understanding the affect probability has on choosing solution values. Coding recommendations for improving your code to get better results are provided. To read more, click here. » read more

Blog Review: Oct. 14


Arm's Hongsup Shin explains a machine learning application that can determine which tests are most likely to find hardware bugs, improving efficiency and reducing the number of tests that need to be run. Synopsys' Pieter van der Wolf and Dmitry Zakharov take a look at the increasing need for low power processors optimized for machine learning tasks as IoT, smart home, and wearable devices pr... » read more

Secure Silicon Lifecycle Management Architecture For Functional Safety


The rapid growth of electronics for automotive applications fueled by advanced ADAS systems pose new challenges for complex SoC design and Silicon Lifecycle Management (SLM) in the supply chain as well as in-field monitoring and management of the population of chips. In these modern complex devices, ensuring the correct and safe operation requires not only functional safety to check for reli... » read more

Sensor Fusion Challenges In Cars


The automotive industry is zeroing in on sensor fusion as the best option for dealing with the complexity and reliability needed for increasingly autonomous vehicles, setting the stage for yet another shift in how data from multiple devices is managed and utilized inside a vehicle. The move toward greater autonomy has proved significantly more complicated than anyone expected at first. There... » read more

Are FPGAs More Secure Than Processors?


Security concerns often focus on software being executed on processors. But not all electronic functionality runs in software. FPGAs provide another way to do work, and they can be more secure than functions executed in software. FPGAs provide more control of hardware and are more opaque to attackers. In the case of embedded FPGAs, the designer is in complete control of the entire system. Th... » read more

The Advantages Of MBSE-Driven E/E Architecture


Vehicles in all sectors are growing in complexity as OEMs develop sophisticated platforms with growing levels of automation and connectivity. To cope with this growing complexity, automotive, aerospace and commercial vehicle OEMs must evolve their architectural design processes to leverage MBSE and the digital thread. Today’s E/E system engineering solutions help companies implement MBSE by p... » read more

Blog Review: Oct. 7


In a blog for Arm, University of Southampton PhD student Sivert Sliper looks at how energy-driven and intermittent computing could be used to power trillions of IoT devices and introduces a SystemC-based simulator for such systems. Mentor's Chris Spear explains why transaction classes should extend from uvm_sequence_item rather than uvm_transaction when designing UVM testbenches. Cadence'... » read more

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