Performance, Power and Area (PPA) are the commonly touted metrics in the semiconductor industry placing PPA among the most widely used acronyms relating to chip development. And rightly so as these three metrics greatly impact all electronic products that are developed. The degree of impact depends of course on the specific … Read More
Tag: machine learning
Quadric’s Chimera GPNPU IP Blends NPU and DSP to Create a New Category of Hybrid SoC Processor
Ask the Expert: Leveraging Machine Learning Capabilities with Altair Feko and Altair HyperStudy
Altair Feko is a well-known and trusted numerical analysis tool for a wide range of problems in electromagnetics. Its efficient solvers make it a very good tool to utilize as part of a process that explores solution spaces or performs advanced optimisation tasks in electromagnetics. Altair HyperStudy makes a strong complement… Read More
Intellectual Abilities of Artificial Intelligence (AI)
To understand AI’s capabilities and abilities we need to recognize the different components and subsets of AI. Terms like Neural Networks, Machine Learning (ML), and Deep Learning, need to be define and explained.
In general, Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed… Read More
CadenceTECHTALK: Find more Bugs, Hit the Most Difficult Scenarios Faster
Date: Thursday, September 29, 2022
Time: 09:00 BST / 10:00 CEST / 11:00 EEST and Israel
Crack the Verification Double Trouble! Chips are becoming bigger and more complex, adding to already existing verification woes. Design and verification engineers struggle with running billions of regression cycles to achieve the desired
Machine Learning in the Fab at #59DAC
It used to be true that a foundry or fab would create a set of DRC files, provide them to designers, and then the process yield would be acceptable, however if the foundry knows more details about the physical implementation of IC designs then they can improve the yield. Using a digital twin of the design, process and metrology steps… Read More
Simulation for Pharma Manufacturing – Expert Talks
Using Machine Learning and Simulation for the Optimization of Industrial Bulk Handling Processes – a Case Study on Bin Blending
Tuesday, July 12 | 10:00 AM CEST (Berlin)
Tuesday, July 12 | 11:00 AM EDT (New York)
In this webinar, Stefan Pantaleev, Senior Application Engineer at Altair, will present an efficient virtual
Using AI in EDA for Multidisciplinary Design Analysis and Optimization
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
CEO Interview: Veerbhan Kheterpal of Quadric.io
It was my pleasure to meet Veerbhan Kheterpal. Veerbhan has founded three technology companies and has full stack expertise spanning software to silicon across Edge & Datacenter applications. Currently, he is a CEO & co-founder of quadric.io, a company that has created a new processor architecture for high performance… Read More
Using Machine Learning to Improve EDA Tool Flow Results
Back in 2020 I first learned from Synopsys about how they had engineered a better way to do optimize layouts on digital designs by using machine learning techniques, instead of relying upon manual approaches. The product was named DSO.ai, standing for Design Space Optimization, and it produced a more optimal floor-plan in less… Read More