Is AI Sustainable? Five Ways To Reduce Its Carbon Footprint


Forget adding bunny ears to your selfie; AI has long since grown up and begun tackling tough, environmental problems. Its data-crunching superpowers make it ideal for everything from ocean monitoring to climate change prediction modeling. But training AI models requires vast amounts of energy, so do the benefits outweigh the environmental cost? In short, is AI sustainable? Sustainable AI: fact... » read more

Power Integrity Analysis For High-Performance FPGAs


Efinix high-performance Titanium field-programmable gate arrays (FPGAs) are custom-tailored for the computing demands of mainstream applications, targeting markets from intelligent edge devices to industrial automation to vision systems to edge servers and communications (figure 1). Efinix customers use the Titanium line of FPGAs to ensure their complex, high-performance designs minimize power ... » read more

Easing The CFD Engineer’s Life With Automated Meshing


Mesh generation is where the user’s expertise and ingenuity can influence the convergence and accuracy of a computational fluid dynamics (CFD) solution by selecting mesh type, topology, and cell quality. But with the rush to automate mesh generation, will the control be ripped out of the user’s hand, or will a valuable engineering skill be lost? The extent to which meshing can be automated... » read more

Brrraaap: Full Throttle On Dirt Bike Electrification


On a dirt bike almost any terrain is fair game. Once you hit the back roads, course correcting through open fields or wooded areas to get where you’re going (or not) is easy. These powerful-yet-agile gravel-and-dirt surfing, rock-hopping machines have been identified by some as the undisputed off-road champions — perfect for exploration in places larger vehicles simply can’t go. Dirt b... » read more

Achieving Greater Accuracy In Real-Time Vision Processing With Transformers


Transformers, first proposed in a Google research paper in 2017, were initially designed for natural language processing (NLP) tasks. Recently, researchers applied transformers to vision applications and got interesting results. While previously, vision tasks had been dominated by convolutional neural networks (CNNs), transformers have proven surprisingly adaptable to vision tasks like image cl... » read more

Facing Off Against Growing Chip Design Complexity


The semiconductor industry continues to face incredible pressures to deliver higher levels of performance in a smaller area, with lower power demands. From high-performance systems-on-chip for 5G mobile devices and network infrastructure to the radio-frequency transceivers that enable autonomous vehicles and the industrial Internet of Things, today’s applications demand a reduced profile, pai... » read more

Ready, Set, Go: Outrunning Moore’s Law With 3D-IC


By Anthony Mastroianni and Gordon Allan, Siemens EDA 3D ICs are an exciting and promising extension of heterogeneous advanced package technology into the third dimension. Although far from mainstream, 3D IC’s time is coming, as chiplet standardization efforts and supporting tool developments begin to make 3D IC practicable and profitable to more players – big and small – and products w... » read more

Edge AI And Chiplets


In the near future, more edge artificial intelligence (AI) solutions will find their way into our lives. This will be especially true in the private sector for applications in the field of voice input and analysis of camera data, which will become well-established. These application areas require powerful AI hardware to be able to process the corresponding continuously accumulating data volumes... » read more

Boosting Data Center Memory Performance In The Zettabyte Era With HBM3


We are living in the Zettabyte era, a term first coined by Cisco. Most of the world’s data has been created over the past few years and it is not set to slow down any time soon. Data has become not just big, but enormous! In fact, according to the IDC Global Datasphere 2022-2026 Forecast, the amount of data generated over the next 5 years will be at least 2x the amount of data generated over ... » read more

Don’t Let Your ML Accelerator Vendor Tell You The ‘F-Word’


Machine learning (ML) inference in devices is all the rage. Nearly every new system on chip (SoC) design start for mobile phones, tablets, smart security cameras, automotive applications, wireless systems, and more has a requirement for a hefty amount of ML capability on-chip. That has silicon design teams scrambling to find ML processing power to add to the existing menu of processing engines ... » read more

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