A New Dawn For IP


The IP industry is changing again. The concept started as build once, use everywhere, but today it is more like architect once, customize everywhere. Few designs can afford sub-optimal IP for their application. The need for customized IP is driven by both leading-edge designs and the trailing markets, although for different reasons. While this customization is causing IP companies to transfo... » read more

Hardware-Software Co-Design Reappears


The core concepts in hardware-software co-design are getting another look, nearly two decades after this approach was first introduced and failed to catch on. What's different this time around is the growing complexity and an emphasis on architectural improvements, as well as device scaling, particularly for AI/ML applications. Software is a critical component, and the more tightly integrate... » read more

HW/SW Design At The Intelligent Edge


Adding intelligence to the edge is a lot more difficult than it might first appear, because it requires an understanding of what gets processed where based on assumptions about what the edge actually will look like over time. What exactly falls under the heading of Intelligent Edge varies from one person to the next, but all agree it goes well beyond yesterday’s simple sensor-based IoT dev... » read more

More Performance At The Edge


Shrinking features has been a relatively inexpensive way to improve performance and, at least for the past few decades, to lower power. While device scaling will continue all the way to 3nm and maybe even further, it will happen at a slower pace. Alongside of that scaling, though, there are different approaches on tap to ratchet up performance even with chips developed at older nodes. This i... » read more

Where ML Works Best


Anirudh Devgan, president of Cadence, sat down with Semiconductor Engineering to discuss machine learning inside and outside of EDA tools and how that will affect the future of chip and system design. What follows are excerpts of that discussion. SE: How do you see the market and use of machine learning shaping up? Devgan: There are three main areas—machine learning inside, machine lear... » read more

Custom Hardware Thriving


In the early days of the IoT, predictions about the commoditization of hardware and the end of customized hardware were everywhere. Several years later, those predictions are being proven wrong. Off-the-shelf components have not replaced customized hardware, and software has not dictated all designs. In fact, in many cases the exact opposite has happened. And where software does play an elev... » read more

Tuning Heterogeneous SoCs


It's one thing to pack multiple processor cores into a design, but it is much more difficult to ensure the hardware matches the software's requirements, or that the software optimally uses the hardware. Both the hardware and software teams are now facing these issues, and there are few tools to help them fully understand the problems or to provide solutions. Design teams continue to add more... » read more

Optimizing Multiple IoT Layers


As the number of connected devices rises, so do questions about how to optimize them for target markets, how to ensure they play nicely together, and how to bring them to market quickly and inexpensively. [getkc id="76" kc_name="IoT"] is broad term that encompasses a lot of disparate pieces for devices, systems, and connected systems. At the highest levels are hardware and software, but with... » read more

Reflections On 2015


It is easy to make predictions, but few people can make them with any degree of accuracy. Most of the time, those predictions are forgotten by the end of the year and there is no one to do a tally of who holds more credibility for next year. Not so with SemiEngineering. We like to hold people's feet to the fire, but while the Pants-On-Fire meter may be applicable to politicians, we like to thin... » read more

Is HW Or SW Running the Show?


In the past, hardware was designed and then passed over to the software team for them to add their contribution to the product. This worked when the amount of software content was small and the practice did not significantly contribute to product delays. Over time, the software content grew and today it is generally accepted that software accounts for more product expense than hardware, takes l... » read more

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