EDA, IP Grow 16.3%


EDA and IP revenue rebounded in Q1, with all geographies reporting increases, according to the ESD Alliance Market Statistics Service. Total revenue increased to 16.3% to $2.606 billion, up from $2.241 billion in the same period in 2018. The global numbers do not reflect the impact of a trade war between the United States and China, which occurred in Q2, but they do point to a significant re... » 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

Blog Review: July 3


Cadence's Paul McLellan digs into 5G with a two-part post explaining the basics of the technology, what makes it so different from 4G, and the challenges ahead including the limitations of mmWave. Synopsys' Vikramjeet Bamel and Pankaj Sharma note the features that make GDDR6 a dominant memory in the high performance segment and allowing it to expand beyond graphics to automotive, AI, and AR/... » read more

Edge Complexity To Grow For 5G


Edge computing is becoming as critical to the success of 5G as millimeter-wave technology will be to the success of the edge. In fact, it increasingly looks as if neither will succeed without the other. 5G networks won’t be able to meet 3GPP’s 4-millisecond-latency rule without some layer to deliver the data, run the applications and broker the complexities of multi-tier Internet apps ac... » read more

Machine Learning Inferencing Moves To Mobile Devices


It may sound retro for a developer with access to hyperscale data centers to discuss apps that can be measured in kilobytes, but the emphasis increasingly is on small, highly capable devices. In fact, Google staff research engineer Pete Warden points to a new app that uses less than 100 kilobytes for RAM and storage, creates an inference model smaller than 20KB, and which is capable of proce... » read more

How To Automate Functional Safety


Semiconductor Engineering sat down to discuss functional safety thinking, techniques and approaches to automation with Mike Stellfox, Fellow at Cadence; Bryan Ramirez, strategic marketing manager at Mentor, a Siemens Business; Jörg Grosse, product manager for functional safety at OneSpin Solutions; and Marc Serughetti, senior director of product marketing for automotive verification solutions ... » read more

How To Solve Automotive Electrical Design Challenges To Get To Market Faster


By Dan Scott and Ulrike Hoff The never-ending development of new technologies in the automotive industry has led to the Content Dilemma, the conflict between the technology content that vehicle manufacturers try to integrate into their vehicles, and the weight, cost and packaging space required for wiring harnesses. Current technology trends driving the Content Dilemma include electrificatio... » read more

Automotive Trends Create New Challenges For Wiring Harness Development


The rapid introduction of new technologies and the influx of automotive start-ups into the market has led to a multitude of challenges for harness development. OEMs and startups alike must consider the number and sophistication of technology features they integrate into their vehicles as they have a direct effect on harness weight, bundle diameter, and cost. Electrification, autonomous drive an... » read more

Week In Review: Design, Low Power


VESA published the DisplayPort 2.0 standard, which allows for a max payload of 77.37 Gbps, a 3X increase in data bandwidth performance compared to DisplayPort 1.4a. The latest release also includes capabilities to address beyond 8K resolutions, higher refresh rates and HDR support at higher resolutions, multiple display configurations, and support for 4K-and-beyond VR resolutions. It is backwar... » read more

Providing An AI Accelerator Ecosystem


A key design area for AI systems is the creation of Machine Learning (ML) algorithms that can be accelerated in hardware to meet power and performance goals. Teams designing these algorithms find out quickly that a traditional RTL design flow will no longer work if they want to meet their delivery schedules. The algorithms are often subject to frequent changes, the performance requirements may ... » read more

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