Power/Performance Bits: April 6


Durian supercapacitors Researchers from the University of Sydney developed a method that uses durian and jackfruit waste to create supercapacitors. Supercapacitors are capable of quickly storing and discharging energy. The team says their fruit-based material is more efficient than ones typically made from activated carbon. "Using durian and jackfruit purchased from a market, we conver... » read more

Power/Performance Bits: March 31


Tellurium transistors Researchers from Purdue University, Washington University in St Louis, University of Texas at Dallas, and Michigan Technological University propose the rare earth element tellurium as a potential material for ultra-small transistors. Encapsulated in a nanotube made of boron nitride, tellurium helps build a field-effect transistor with a diameter of two nanometers. ... » read more

Power/Performance Bits: March 24


Backscatter Wi-Fi radio Engineers at the University of California San Diego developed an ultra-low power Wi-Fi radio they say could enable portable IoT devices. Using 5,000 times less power than standard Wi-Fi radios, the device consumes 28 microwatts while transmitting data at a rate of 2 megabits per second over a range of up to 21 meters. "You can connect your phone, your smart devices, ... » read more

Designing Resilient Electronics


Electronic systems in automobiles, airplanes and other industrial applications are becoming increasingly sophisticated and complex, required to perform an expanding list of functions while also becoming smaller and lighter. As a result, pressure is growing to design extremely high-performance chips with lower energy consumption and less sensitivity to harsh environmental conditions. If this ... » read more

Power/Performance Bits: March 17


MRAM speed Researchers at ETH Zurich and Imec investigated exactly how quickly magnetoresistive RAM (MRAM) can store data. In the team's MRAM, electrons with opposite spin directions are spatially separated by the spin-orbit interaction, creating an effective magnetic field that can be used to invert the direction of magnetization of a tiny metal dot. "We know from earlier experiments, i... » read more

HBM Issues In AI Systems


All systems face limitations, and as one limitation is removed, another is revealed that had remained hidden. It is highly likely that this game of Whac-A-Mole will play out in AI systems that employ high-bandwidth memory (HBM). Most systems are limited by memory bandwidth. Compute systems in general have maintained an increase in memory interface performance that barely matches the gains in... » read more

Week In Review: Auto, Security, Pervasive Computing


AI, machine learning Cadence says it has optimized its Tensilica HiFi digital signal processor IP to efficiently execute TensorFlow Lite for Microcontrollers, which are used in Google’s machine learning platform for edge. This means developers of AI/ML on the edge systems can now put better audio processing on edge devices with ML applications like keyword detection, audio scene detection, n... » read more

How Much Power Will AI Chips Use?


AI and machine learning have voracious appetites when it comes to power. On the training side, they will fully utilize every available processing element in a highly parallelized array of processors and accelerators. And on the inferencing side they, will continue to optimize algorithms to maximize performance for whatever task a system is designed to do. But as with cars, mileage varies gre... » read more

Packaging And Package Design For AI At The Edge


Industrial applications will acquire significantly more data directly from machines in coming years. To properly handle this increase in data, it must already be prepared at the machine. The data of the individual sensors can be processed, or an initial data merger can take place here at the so-called “edge.” Algorithms and methods from the field of artificial intelligence increasingly a... » read more

HBM2E Memory: A Perfect Fit For AI/ML Training


Artificial Intelligence/Machine Learning (AI/ML) growth proceeds at a lightning pace. In the past eight years, AI training capabilities have jumped by a factor of 300,000 (10X annually), driving rapid improvements in every aspect of computing hardware and software. Memory bandwidth is one such critical area of focus enabling the continued growth of AI. Introduced in 2013, High Bandwidth Memo... » read more

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