Week In Review: Semiconductor Manufacturing, Test


The global sales slump in semiconductors but may be stabilizing, according to a new report from the Semiconductor Industry Association (SIA). Worldwide sales of semiconductors fell 8.7% in Q1 2023 compared to the Q4 2022, and dropped 21.3% compared to the Q1 2022. Sales for the month of March 2023 increased 0.3% compared to February 2023. Meanwhile, SEMI reports worldwide silicon wafer shipment... » read more

Week In Review: Design, Low Power


Arm advanced its progress toward an initial public offering, confidentially submitting a draft registration statement on Form F-1 to the U.S. Securities and Exchange Commission. The size and price range for the proposed offering have yet to be determined. Graphene IDM Paragraf acquired Cardea Bio, a maker of graphene-based biocompatible chips. Cardea has developed a biosignal processing unit... » read more

Week In Review: Auto, Security, Pervasive Computing


Pervasive computing Microsoft and AMD are working together on an AI processor, according to a report in Bloomberg. Tenstorrent adopted Arteris IP’s Ncore and FlexNoC interconnect IP for its AI RISC-V chiplets. The chiplets will be configurable for different uses and workloads. Some use cases include AI high-performance computing for data center, such as cloud servers, and edge devices and... » read more

How Safe Is Safe Enough?


That was the overarching question a group of 180 experts discussed last week at the ISO 26262 & SOTIF conference for four days during #FuSaWeek2023 in Berlin. "How Safe is Safe Enough" is also the title of Prof. Koopman's book from September 2022. I mentioned him in my blog "Are We Too Hard On Artificial Intelligence For Autonomous Driving?" Prof. Koopman was referenced often in Berlin, and... » read more

ML Automotive Chip Design Takes Off


Machine learning is increasingly being deployed across a wide swath of chips and electronics in automobiles, both for improving reliability of standard parts and for the creation of extremely complex AI chips used in increasingly autonomous applications. On the design side, the majority of EDA tools today rely on reinforcement learning, a machine learning subset of AI that teaches a machine ... » read more

Going Virtual In Automotive Electronics Development


Developing the electrical/electronic (E/E) systems in automobiles and other vehicles has always been challenging due to the rough environmental conditions experienced on the road and the high expectations for safety and reliability. In recent years, these challenges have been exacerbated by several industry trends. They have triggered a revolution in how electronic control units (ECUs) are desi... » read more

Data Leakage Becoming Bigger Issue For Chipmakers


Data leakage is becoming more difficult to stop or even trace as chips become increasingly complex and heterogeneous, and as more data is stored and utilized by chipmakers for other designs. Unlike a cyberattack, which typically is done for a specific purpose, such as collecting private data or holding a system ransom, data leaks can spring up anywhere. And as the value of data increases, th... » read more

Hardware-Based Cybersecurity For Software-Defined Vehicles


As vehicle technology advances, so does the complexity of the electrical/electronic systems within these smart vehicles. A software-defined vehicle (SDV) relies on centralized compute and an advanced software stack to control most of its functionality, from engine performance to infotainment systems. SDVs are becoming more important as automakers look to improve vehicle performance, reduce emis... » read more

Role Of IoT Software Expanding


IoT software is becoming much more sophisticated and complex as vendors seek to optimize it for specific applications, and far more essential for vendors looking to deliver devices on-time and on-budget across multiple market segments. That complexity varies widely across the IoT. For example, the sensor monitoring for a simple sprinkler system is far different than the preventive maintenanc... » read more

Issues And Challenges In Super-Resolution Object Detection And Recognition


If you want high performance AI inference, such as Super-Resolution Object Detection and Recognition, in your SoC the challenge is to find a solution that can meet your needs and constraints. You need inference IP that can run the model you want at high accuracy. You need inference IP that can run the model at the frame rate you want: higher frame rate = lower latency, more time for dec... » read more

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