How Secure Are FPGAs?


The unique hybrid software/hardware nature of FPGAs makes them tempting targets for cyberattacks, while also enabling them to rebuff attacks and change the attack surface before significant damage can be done. But it's becoming increasingly challenging to address all the potential vulnerabilities. FPGAs are often included in larger systems, each with their own unique attack vectors as well a... » read more

Trendspotting: Automotive IC Startup Funding In 2023


Consumers expect a lot from the electronics in their cars. The parts in the safety-critical systems need to be reliable for up to 18 years, able to handle a range of temperatures, voltages, and vibrations — and all the while be fault-tolerant and make zero errors. On top of those basic requirements, automakers trying to appeal to consumers are adding in more features that communicate with the... » read more

Money Pours Into New Fabs And Facilities


Fabs, packaging, test and assembly, and R&D all drew major funding in 2023. Companies poured money into offshore locations, such as India and Malaysia, to access a larger workforce and lower costs, while also partnering with governments to secure domestic supply chains amid ongoing geopolitical turmoil. Looking ahead, artificial intelligence (AI), quantum computing, and data applications... » read more

Top Tech Videos of 2023


In 2023, heterogeneous integration, RISC-V, and advanced node logic scaling and advanced packaging dominated the semiconductor industry. All of those topics spurred deep discussions at conferences, and they were the subject of Semiconductor Engineering's most popular videos. Of the videos published in 2023, here are the highlights from our five channels: Manufacturing, Packaging & Mater... » read more

A New Approach For Sensor Design


Pawel Malinowski, program manager at imec, sat down with Semiconductor Engineering to discuss what's changing in sensor technology and why. What follows are excerpts of that discussion. SE: What's next for sensor technology? Malinowski: We are trying to find a new way of making image sensors because we want to get out of the limitations of silicon photodiodes. Silicon is a perfect materi... » read more

Analog Design Complicates Voltage Droop


Experts at the Table: Semiconductor Engineering sat down to talk about voltage droop in analog and mixed-signal designs, and the need for multi-vendor tool interoperability and more precision, with Bill Mullen, distinguished engineer at Ansys; Rajat Chaudhry, product management group director at Cadence; Heidi Barnes, senior applications engineer at Keysight; Venkatesh Santhanagopalan, product ... » read more

RISC-V Micro-Architectural Verification


RISC-V processors are garnering a lot of attention due to their flexibility and extensibility, but without an efficient and effective verification strategy, buggy implementations may lead to industry problems. Prior to RISC-V, processor verification almost became a lost art for most semiconductor companies. Expertise was condensed into the few commercial companies that provided processors or... » read more

Dramatic Changes Ahead For Chips And Systems


Early this year, most people had never heard of generative AI. Now the entire world is racing to capitalize on it, and that's just the beginning. New markets, such as spatial computing, quantum computing, 6G, smart infrastructure, sustainability, and many more are accelerating the need to process more data faster, more efficiently, and with much more domain specificity. Compared to the days ... » read more

2023: A Good Year For Semiconductors


Looking back, 2023 has had more than its fair share of surprises, but who were the winners and losers? The good news is that by the end of the year, almost everyone was happy. That is not how we exited 2022, where there was overcapacity, inventories had built up in many parts of the industry, and few sectors — apart from data centers — were seeing much growth. The supposed new leaders we... » read more

Fabs Begin Ramping Up Machine Learning


Fabs are beginning to deploy machine learning models to drill deep into complex processes, leveraging both vast compute power and significant advances in ML. All of this is necessary as dimensions shrink and complexity increases with new materials and structures, processes, and packaging options, and as demand for reliability increases. Building robust models requires training the algorithms... » read more

← Older posts Newer posts →