One aspect of received wisdom on AI has been that all the innovation starts in the big machine learning/training engines in the cloud. Some of that innovation might eventually migrate in a reduced/ limited form to the edge. In part this reflected the newness of the field. Perhaps also in part it reflected need for prepackaged one-size-fits-many… Read More
Tag: AI
AI for EDA for AI
I’ve been noticing over the last few years that electronic design automation (EDA) vendors just love to talk about artificial intelligence (AI) and machine learning (ML), sometimes with deep learning (DL) and neural networks tossed in as well. It can get a bit confusing since these terms are used in two distinct contexts. The first… Read More
Edge Computing Paradigm
Edge computing is a model in which data, processing and applications are concentrated in devices at the network rather than existing almost entirely in the cloud.
Edge Computing is a paradigm that extends Cloud Computing and services to the of the network, similar to Cloud, Edge provides data, compute, storage, and application… Read More
Big Data Helps Boost PDN Sign Off Coverage
The nearly unavoidable truth about dynamic voltage drop (DVD) signoff for power distribution networks (PDN) is that the quality of results depends on the quality and quantity of the vectors used to activate the circuit switching. As SOCs grow larger and are implemented on smaller nodes, the challenges of sufficient coverage … Read More
Synopsys Expands into Silicon Lifecycle Management
I spoke with Steve Pateras of Synopsys last week to better understand what was happening with their Silicon Lifecycle Management vision, and I was reminded of a Forbes article from last year: Never Heard of Silicon Lifecycle Management? Join the Club. At least two major EDA vendors are now using the relatively new acronym SLM, and… Read More
A Flexible and Efficient Edge-AI Solution Using InferX X1 and InferX SDK
The Linley Group held its Fall Processor Conference 2021 last week. There were several informative talks from various companies updating the audience on the latest research and development work happening in the industry. The presentations were categorized as per their focus, under eight different sessions. The sessions topics… Read More
Neural Network Growth Requires Unprecedented Semiconductor Scaling
The truth is that we are just at the beginning of the Artificial Intelligent (AI) revolution. The capabilities of AI are just now starting to show hints of what the future holds. For instance, cars are using large complex neural network models to not only understand their environment, but to also steer and control themselves. For… Read More
Optimize AI Chips with Embedded Analytics
The foundry model, multi-source IP blocks, advanced packaging technologies, cloud computing, hyper-connectivity and access to open-source software have all contributed to the incredible electronics products of recent times. Along with this, the complexity of developing and taking a chip to market has also increased. And… Read More
The Quest for Bugs: “Correct by Design!”
In this article we take an objective view of Virtual Prototyping from the engineering lens and the “quest to find bugs”. In this instance we discuss the avoidance of bugs in terms of architecting complex ASICs to be “correct by design”.
AI Challenges
It is not surprising to find out that other areas of human endeavour, beyond semiconductor… Read More
Enabling Silicon Technologies to Address Automotive Radar Trends and Requirements
During the week of April 19th, Linley held its Spring Processor Conference 2021. The Linley Group has a reputation for putting on excellent conferences. And this year’s spring conference was no exception. There were a number of very informative talks from various companies updating the audience on the latest research and development… Read More