Memory Options And Tradeoffs


Steven Woo, Rambus fellow and distinguished inventor, talks with Semiconductor Engineering about different memory options, why some are better than others for certain tasks, and what the tradeoffs are between the different memory types and architectures.     Related Articles/Videos Memory Tradeoffs Intensify In AI, Automotive Applications Why choosing memories and archi... » read more

How To Manage DFT For AI Chips


Semiconductor companies are racing to develop AI-specific chips to meet the rapidly growing compute requirements for artificial intelligence (AI) systems. AI chips from companies like Graphcore and Mythic are ASICs based on the novel, massively parallel architectures that maximize data processing capabilities for AI workloads. Others, like Intel, Nvidia, and AMD, are optimizing existing archite... » read more

Week in Review: IoT, Security, Auto


Internet of Things Cattle ranchers in Australia are using solar-powered ear tags to keep track of their herds, connecting through LoRa technology to locate their bulls, cows, heifers, and steers. SODAQ of the Netherlands and Lacuna Space of the U.K. are providing the Internet of Things technology and satellite-based LoRa connectivity to make this possible. “The main differentiator for LoRa o... » read more

Week in Review: IoT, Security, Auto


Internet of Things McKinsey & Company identified 10 top trends in the Internet of Things. They include: IoT is a business opportunity, not just a tech opportunity; disciplined execution across multiple use cases is the path to value; and IoT is gradually enabling more subscription business models, but consumers are resistant. Louis Columbus of IQMS provides some IoT data points and id... » read more

Week In Review: Design, Low Power


Gyrfalcon Technology released a 22nm AI accelerator ASIC chip with embedded MRAM. The Lightspeeur 2802M includes 40MB of memory to support large or multiple AI models, such as image classification and voice identification, within a single chip. Manufactured by TSMC, target applications include IoT endpoints, cloud solutions, and autonomous vehicles. Arm expanded its line of automotive-focuse... » read more

Week In Review: Design, Low Power


Tools & IP Cadence unveiled deep neural-network accelerator (DNA) AI processor IP, Tensilica DNA 100, targeted at on-device neural network inference applications. The processor is scalable from 0.5 TMAC (Tera multiply-accumulate) to 12 TMACs, or 100s of TMACs with multiple processors stacked, and the company claims it delivers up to 4.7X better performance and up to 2.3X more performance p... » read more

Week in Review: IoT, Security, Auto


Internet of Things Release 3 is published by oneM2M, the worldwide Internet of Things interoperability standards initiative. The third set of specifications deals with 3GPP interworking, especially as it relates to cellular IoT connectivity, among other features. The release is said to enable seamless interworking with narrowband IoT and LTE-M connectivity through the 3GPP Service Capability E... » read more

The Week in Review: IoT


Market Research International Data Corp. (IDC) forecasts the worldwide Internet of Things market will double from $625.2 billion in 2015 to $1.29 trillion in 2020 for a compound annual growth rate of 15.6%. Aeris collaborated with IDC on its report, which predicts the installed base of IoT endpoints will increase from 12.1 billion at the end of 2015 to more than 30 billion by 2020. Initiati... » read more

The Week In Review: Manufacturing


Samsung Austin Semiconductor plans to invest more than $1 billion in its fab in Austin, Texas. Today, the fab continues to ramp up the company’s 14nm finFET technology. At the same time, Samsung is expanding its advanced finFET foundry process technology offerings with its fourth-generation 14nm process (14LPU) and its third-generation 10nm technology (10LPU). Graphcore is developing a so-... » read more