Dealing With Sub-Threshold Variation


Chipmakers are pushing into sub-threshold operation in an effort to prolong battery life and reduce energy costs, adding a whole new set of challenges for design teams. While process and environmental variation long have been concerns for advanced silicon process nodes, most designs operate in the standard “super-threshold” regime. Sub-threshold designs, in contrast, have unique variatio... » read more

Semiconductor Memory Evolution And Current Challenges


The very first all-electronic memory was the Williams-Kilburn tube, developed in 1947 at Manchester University. It used a cathode ray tube to store bits as dots on the screen’s surface. The evolution of computer memory since that time has included numerous magnetic memory systems, such as magnetic drum memory, magnetic core memory, magnetic tape drive, and magnetic bubble memory. Since the 19... » read more

China Speeds Up Advanced Chip Development


China is accelerating its efforts to advance its domestic semiconductor industry, amid ongoing trade tensions with the West, in hopes of becoming more self-sufficient. The country is still behind in IC technology and is nowhere close to being self-reliant, but it is making noticeable progress. Until recently, China’s domestic chipmakers were stuck with mature foundry processes with no pres... » read more

Memory Issues For AI Edge Chips


Several companies are developing or ramping up AI chips for systems on the network edge, but vendors face a variety of challenges around process nodes and memory choices that can vary greatly from one application to the next. The network edge involves a class of products ranging from cars and drones to security cameras, smart speakers and even enterprise servers. All of these applications in... » read more

Taming Novel NVM Non-Determinism


New memory technologies may have non-deterministic characteristics that add calibration to the test burden — and may require recalibration during their lifetime. Many of these memories are in development as a result of the search for a storage-class memory (SCM) technology that can bridge the gap between larger, slower memories like flash and faster DRAM memory. There are several approache... » read more

Why Standard Memory Choices Are So Confusing


System architects increasingly are developing custom memory architectures based upon specific use cases, adding to the complexity of the design process even though the basic memory building blocks have been around for more than half a century. The number of tradeoffs has skyrocketed along with the volume of data. Memory bandwidth is now a gating factor for applications, and traditional memor... » read more

Utilizing Computational Memory


For systems to become faster and consume less power, they must stop wasting the power required to move data around and start adding processing near memory. This approach has been proven, and products are entering the marketplace designed to fill a number of roles. Processing near memory, also known as computational memory, has been hiding in the shadows for more than a decade. Ever since the... » read more

Power/Performance Bits: April 16


Faster CNN training Researchers at North Carolina State University developed a technique that reduces training time for deep learning networks by more than 60% without sacrificing accuracy. Convolutional neural networks (CNN) divide images into blocks, which are then run through a series of computational filters. In training, this needs to be repeated for the thousands to millions of images... » read more

3D NAND Metrology Challenges Growing


3D NAND vendors face several challenges to scale their devices to the next level, but one manufacturing technology stands out as much more difficult at each turn—metrology. Metrology, the art of measuring and characterizing structures, is used to pinpoint problems and ensure yields for all chip types. In the case of 3D NAND, the metrology tools are becoming more expensive at each iteration... » read more

January ’19 Startup Funding: $100M+ Rounds Abound


Sixteen companies received private funding rounds of $100 million or more during the month of January, with two privately held companies, Infor and Verily Life Sciences, taking in rounds of $1.5 billion and $1 billion, respectively. The market segments represented in the January rounds were varied. Multiple companies using artificial intelligence technology in their offerings and cloud-based... » read more

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