Balancing Training, Quantization, And Hardware Integration In NPUs


Experts At The Table: AI/ML is driving a steep ramp in neural processing unit (NPU) design activity for everything from data centers to edge devices such as PCs and smartphones. Semiconductor Engineering sat down to discuss this with Jason Lawley, director of product marketing, AI IP at Cadence; Sharad Chole, chief scientist and co-founder at Expedera; Steve Roddy, chief marketing officer at Qu... » read more

Addressing Critical Tradeoffs In NPU Design


Experts At The Table: AI/ML are driving a steep ramp in neural processing unit (NPU) design activity for everything from data centers to edge devices such as PCs and smartphones. Semiconductor Engineering sat down with Jason Lawley, director of product marketing, AI IP at Cadence; Sharad Chole, chief scientist and co-founder at Expedera; Steve Roddy, chief marketing officer at Quadric; Steven W... » read more

How And Why To Optimize NPUs


Experts At The Table: AI/ML are driving a steep ramp in neural processing unit (NPU) design activity for everything from data centers to edge devices such as PCs and smartphones.  Semiconductor Engineering sat down with Jason Lawley, director of product marketing, AI IP at Cadence; Sharad Chole, chief scientist and co-founder at Expedera; Steve Roddy, chief marketing officer at Quadric; Steven... » read more

A Hybrid Subsystem Architecture To Elevate Edge AI


The world of artificial intelligence is moving beyond the cloud and into our everyday devices from smart sensors to robotics and AR/VR headsets. One of the key components that enables this shift is a neural processing unit (NPU), also known as an AI accelerator, which is a specialized hardware designed to execute AI models. Optimized for neural network, deep learning, and machine learning tasks... » read more

Will New Processor Architectures Raise Energy Efficiency?


Data centers continue to heat up as new processors consume more energy than ever before. Cooling is the primary weapon against the heat these processors generate, but it won’t be able to keep up forever with traditional processor architectures. New ones may be necessary. There are opportunities today to make well-known architectures more energy-efficient, but the number of options for subs... » read more

That’s Not A DSP!


In the 1986 hit comedy movie "Crocodile Dundee," the title character – a rough and tumble Australian transported to the mean streets of New York City – is confronted by street thugs brandishing a switchblade knife who demand his wallet. In response he cooly smirks and pulls a knife out of his belt that is 10 times the size of the would-be assailants’ weapon and delivers the signature line... » read more

The Coming NPU Population Collapse


At some point in everyone’s teenage years of schooling we were all taught in a nature or biology class about cycles of population surges and then inevitable population collapses. Whether the example was an animal, plant, insect or even bacteria, some external event triggers a rapid surge in the population of a species which leads to overpopulation and competition for resources (food, space, s... » read more

The Rise Of Generative AI On The Edge


Artificial intelligence (AI) and machine learning (ML) have undergone significant transformations over the past decade. The revolution of convolutional neural networks (CNNs) and recurrent neural networks (RNNs) is evolving toward the adoption of transformers and generative AI (GenAI), marking a pivotal shift in the field. This transition is driven by the need for more accurate, efficient, and ... » read more

To (B)atch Or Not To (B)atch?


When evaluating benchmark results for AI/ML processing solutions, it is very helpful to remember Shakespeare’s Hamlet, and the famous line: “To be, or not to be.” Except in this case the “B” stands for Batched. Batch size matters There are two different ways in which a machine learning inference workload can be used in a system. A particular ML graph can be used one time, preced... » read more

Embrace The New!


The ResNet family of machine learning algorithms was introduced to the AI world in 2015. A slew of variations was rapidly discovered that at the time pushed the accuracy of ResNets close to the 80% threshold (78.57% Top 1 accuracy for ResNet-152 on ImageNet). This state-of-the-art performance at the time, coupled with the rather simple operator structure that was readily amenable to hardware ac... » read more

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