tag: ML

GDDR6 Memory Enables High-Performance AI/ML Inference
By Frank Ferro - 10 Nov, 2022 - Comments: 0

A rapid rise in the size and sophistication of inference models has necessitated increasingly powerful hardware deployed at the network edge and in endpoint devices. To keep these inference processors and accelerators fed with data requires a state-of-the-art memory that delivers extremely high bandwidth. This blog will explore how GDDR6 supports the memory and performance requirements of artif... » read more

Securing Accelerator Blades For Datacenter AI/ML Workloads
By Emma-Jane Crozier - 25 Oct, 2022 - Comments: 0

Data centers handle huge amounts of AI/ML training and inference workloads for their individual customers. Such a vast number of workloads calls for efficient processing, and to handle these workloads we have seen many new solutions emerge in the market. One of these solutions is pluggable accelerator blades, often deployed in massively parallel arrays, that implement the latest state-of-the-ar... » read more

Auto Safety Tech Adds New IC Design Challenges
By John Koon - 06 Oct, 2022 - Comments: 1

The role of AI/ML in automobiles is widening as chipmakers incorporate more intelligence into chips used in vehicles, setting the stage for much safer vehicles, fewer accidents, but much more complex electronic systems. While full autonomy is still on the distant horizon, the short-term focus involves making sure drivers are aware of what's going on around them — pedestrians, objects, or o... » read more

Deep Learning To Classify And Establish Structure Property Predictions With PeakForce QNM Atomic Force Microscopy
By Bruker - 07 Sep, 2022 - Comments: 0

Machine learning and specifically, deep learning, is a powerful tool to establish the presence (or absence) of microstructure correlations to bulk properties with its ability to flesh out relationships and trends that are difficult to establish otherwise. This application note discusses the use of deep learning tools, to explore AFM phase and PeakForce Quantitative Nanomechanics (QNM) im... » read more

Challenges Mount In New Autos
By John Koon - 06 Sep, 2022 - Comments: 0

Electronics are becoming the primary differentiator for carmakers, adding an array of options that can alter everything from how a vehicle's occupants interact with their surroundings to how the vehicle drives. But the infrastructure needed to support these features also raises a slew of technology and business questions for which there are no simple answers today. For example, how will new ... » read more

Chipmakers Model AI For Radio Access Networks
By Martha DeGrasse - 22 Aug, 2022 - Comments: 0

The chips that power and connect smartphones are now foundational to a disparate portfolio of daily tasks we take for granted, from accessing the internet to snapping a photo or asking Siri or Google if rain is in the forecast. Most people don’t think twice about the conflicting demands these tasks can place on semiconductors, but for engineers at leading chip manufacturers, this balancing ac... » read more

AI Power Consumption Exploding
By Brian Bailey - 15 Aug, 2022 - Comments: 2

Machine learning is on track to consume all the energy being supplied, a model that is costly, inefficient, and unsustainable. To a large extent, this is because the field is new, exciting, and rapidly growing. It is being designed to break new ground in terms of accuracy or capability. Today, that means bigger models and larger training sets, which require exponential increases in processin... » read more

ML And UVM Share Same Flaws
By Brian Bailey - 28 Jul, 2022 - Comments: 1

A number of people must be scratching their heads over what UVM and machine learning (ML) have in common, such that they can be described as having the same flaws. In both cases, it is a flaw of omission in some sense. Let's start with ML, and in particular, object recognition. A decade ago, Alexnet, coupled with GPUs, managed to beat all of the object detection systems that relied on tradit... » read more

Bespoke Silicon Redefines Custom ASICs
By Ann Mutschler - 28 Jul, 2022 - Comments: 0

Semiconductor Engineering sat down to discuss bespoke silicon and what's driving that customization with Kam Kittrell, vice president of product management in the Digital & Signoff group at Cadence; Rupert Baines, chief marketing officer at Codasip; Kevin McDermott, vice president of marketing at Imperas; Mo Faisal, CEO of Movellus; Ankur Gupta, vice president and general manager of Siemens... » read more

Customization, Heterogenous Integration, And Brute Force Verification
By Ed Sperling - 14 Jul, 2022 - Comments: 0

Semiconductor Engineering sat down to discuss why new approaches are required for heterogeneous designs, with Bari Biswas, senior vice president for the Silicon Realization Group at Synopsys; John Lee, general manager and vice president of the Ansys Semiconductor business unit; Michael Jackson, corporate vice president for R&D at Cadence; Prashant Varshney, head of product for Microsoft Azu... » read more

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