Most IC and system engineers follow a familiar process when designing a new product: create a model, use parameters for the model, simulate the model, observe the results, compare results versus requirements, change the parameters or model and repeat until satisfied or it’s time to tape out. On the EDA side, most tools perform… Read More
Qualcomm is a common name in mobile industry for chips. The company has generated $33 billion in revenue in 2021 and continues to march ahead with its innovations. However, Qualcomm doesn’t get the same visibility and mention as Nvidia and Intel in the world of AI chips. By our estimate, Qualcomm’s contribution to … Read More
Moving deep learning from the cloud to the edge is the holy grail when it comes to deploying highly accurate, low-power applications. Market demand for edge AI continues to grow globally as new hardware and software solutions are now more readily available, enabling any sized company to easily implement deep learning solutions… Read More
Frankwell Lin, Chairman of Andes Technology, started his career being as application engineer in United Microelectronics Corporation (UMC) while UMC was an IDM with its own chip products, he experienced engineering, product planning, sales, and marketing jobs with various product lines in UMC. In 1995, after four years working… Read More
Among the multiple technologies that are poised to deliver substantial value in the future, Artificial Intelligence (AI) tops the list. An IEEE survey showed that AI will drive the majority of innovation across almost every industry sector in the next one to five years.
As a result, the AI revolution is motivating the need for … Read More
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
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 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
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
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
