In Automotive, A Move From Microcontrollers To Massively Complex SoCs


Cars and custom, high-end chips. It’s a topic coming up more frequently these days. The most prominent example is Tesla’s FSD computer, described by Elon Musk as “the best chip in the world…objectively” during the company’s April Autonomy Day. When it comes to chips, Tesla is alone only when it comes to hyperbole, at least based on browsing job postings for big carmakers and supplie... » read more

Can The Hardware Supply Chain Remain Secure?


Malware in computers has been a reality since the 1990s, but lately the focus has shifted to hardware. So far, the semiconductor industry has been lucky because well-publicized threats were either limited or unproven. But sooner or later, luck runs out. Last year saw two significant incidents that shook people’s faith in the integrity of hardware security. The first was the Meltdown/Spectr... » read more

Nvidia to Buy Mellanox for $6.9B


Nvidia reached a definitive agreement to acquire Mellanox Technologies for $125 a share in cash, giving the deal an enterprise value of about $6.9 billion. The proposed transaction would complement Nvidia’s product portfolio in high-performance computing for applications in artificial intelligence and big data analytics, with Mellanox’s specialty in providing interconnects for hyperscale da... » read more

Machine Learning Shifts More Work to FPGAs, SoCs


A wave of machine-learning-optimized chips is expected to begin shipping in the next few months, but it will take time before data centers decide whether these new accelerators are worth adopting and whether they actually live up to claims of big gains in performance. There are numerous reports that silicon custom-designed for machine learning will deliver 100X the performance of current opt... » read more

Democratized Autonomous Vehicle System Design


The major question facing automotive equipment vendors and OEMs working to bring autonomous vehicles to market: how to address the additional cost and power of these new electronic systems while reducing system latency and improving manufacturability? TIRIAS Research says the DRS360 Autonomous Driving Platform provides an answer. To read more, click here. » read more

eSilicon Builds ASIC Business On Leading-Edge Chip Design


How advanced application specific integrated circuits (ASIC) chip design and manufacturing for leading-edge applications such as networking and artificial intelligence can be successfully outsourced. The company which has capabilities in 2.5D packaging, high-bandwidth memories (HBM), and silicon IP for fast memories and SerDes designs. The company has many leading system companies as custome... » read more

eSilicon Builds ASIC Business On Leading-Edge Chip Design


This paper explores how advanced application specific integrated circuits (ASIC) chip design and manufacturing for leading-edge applications such as networking and artificial intelligence can be successfully outsourced. The company we profile is eSilicon, which has capabilities in 2.5D packaging, high-bandwidth memories (HBM), and silicon IP for fast memories and SerDes designs. The company ha... » read more

Lowering The Barriers To Entry For ASICs


The future of IoT and its rate of scalability depends upon increased functionality in the smallest form factors. Arm knows that OEMs are increasingly turning to custom SoCs/ASICs for a wealth of benefits: differentiation, cost savings, improved reliability, and smaller products. So, at Arm, we wanted to better understand the perceived risks involved for OEMs – what makes custom SoCs a task... » read more

Is Design Innovation Slowing?


Paul Teich, principal analyst for Tirias Research, gave a provocative talk at the recent DAC conference entitled, "Is Integration Leaving Less Room for Design Innovation?" The answer isn't as simple as the question might suggest. "Integration used to be a driver for increasing the functionality of silicon," Teich said. "Increasingly, it will be used to incorporate more features of an entire ... » read more

Plugging Holes In Machine Learning


The number of companies using machine learning is accelerating, but so far there are no tools to validate, verify and debug these systems. That presents a problem for the chipmakers and systems companies that increasingly rely on machine learning to optimize their technology because, at least for now, it creates the potential for errors that are extremely difficult to trace and fix. At the s... » read more

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