tag: machine learning

Simulating Reality: The Importance Of Synthetic Data In AI/ML Systems For Radar Applications
By Arien Sligar - 09 Feb, 2023 - Comments: 0

Artificial intelligence and machine learning (AI/ML) are driving the development of next-generation radar perception. However, these AI/ML-based perception models require enough data to learn patterns and relationships to make accurate predictions on new, unseen data and scenarios. In the field of radar applications, the data used to train these models is often collected from real-world meas... » read more

Using Machine Learning To Automate Debug Of Simulation Regression Results
By Synopsys - 08 Feb, 2023 - Comments: 0

Regression failure debug is usually a manual process wherein verification engineers debug hundreds, if not thousands of failing tests. Machine learning (ML) technologies have enabled an automated debug process that not only accelerates debug but also eliminates errors introduced by manual efforts. This white paper discusses how verification engineers can more efficiently analyze, bin, triage... » read more

Achieve 10X Faster CDC Debug Leveraging Machine Learning
By Synopsys - 25 Jan, 2023 - Comments: 0

Over the years, system-on-chip (SoC) design sizes have crossed the billion-gate mark. Higher complexity has been introduced within semiconductor designs to deliver desired functionality. The number of asynchronous clock and reset domains is growing heavily within these complex SoCs, leading to millions of clock domain crossing (CDC) violations at the SoC level. Each of these violations ... » read more

Scatterometry-Based Methodologies For Characterization Of MRAM Technology
By Nova - 18 Jan, 2023 - Comments: 0

Magnetoresistive random-access memory (MRAM) technology and recent developments in fabrication processes have shown it to be compatible with Si-based complementary metal oxide semiconductor (CMOS) technologies. The perpendicular spin transfer torque MRAM (STT-MRAM) configuration opened up opportunities for an ultra-dense MRAM evolution and was most widely adapted for its scalability. Insertion ... » read more

Will Floating Point 8 Solve AI/ML Overhead?
By Karen Heyman - 12 Jan, 2023 - Comments: 2

While the media buzzes about the Turing Test-busting results of ChatGPT, engineers are focused on the hardware challenges of running large language models and other deep learning networks. High on the ML punch list is how to run models more efficiently using less power, especially in critical applications like self-driving vehicles where latency becomes a matter of life or death. AI already ... » read more

Operator Anxiety
By Steve Roddy - 12 Jan, 2023 - Comments: 0

Are you one of the early pioneers who have purchased an electric car? In the United States in Q3 2022, 6% of new vehicle sales were pure electric models. Despite all the hype — and significant purchase subsidies in support of battery cars — today only 1% of the cumulative number of vehicles in service in the US are purely plug-in electric. One of the reasons electric car sales have not full... » read more

Industrial Solutions For Machine-Learning-Enabled Yield Optimization And Test
By Sonny Banwari - 10 Jan, 2023 - Comments: 0

This article summarizes the content of a paper developed and presented by Advantest at ETS 2022. By Sonny Banwari and Matthias Sauer According to market research firm Gartner, Inc., in assessing the completion rate of data science projects, as well as the bottom-line value they generate for their companies, only between 15 and 20 percent of these projects are ever completed. Moreover, of ... » read more

Neural Architecture & Hardware Accelerator Co-Design Framework (Princeton/ Stanford)
By Technical Paper Link - 12 Dec, 2022 - Comments: 0

A new technical paper titled "CODEBench: A Neural Architecture and Hardware Accelerator Co-Design Framework" was published by researchers at Princeton University and Stanford University. "Recently, automated co-design of machine learning (ML) models and accelerator architectures has attracted significant attention from both the industry and academia. However, most co-design frameworks either... » read more

Don’t Let Your ML Accelerator Vendor Tell You The ‘F-Word’
By Steve Roddy - 08 Dec, 2022 - Comments: 0

Machine learning (ML) inference in devices is all the rage. Nearly every new system on chip (SoC) design start for mobile phones, tablets, smart security cameras, automotive applications, wireless systems, and more has a requirement for a hefty amount of ML capability on-chip. That has silicon design teams scrambling to find ML processing power to add to the existing menu of processing engines ... » read more

Systematic Yield Issues Now Top Priority At Advanced Nodes
By Laura Peters - 06 Dec, 2022 - Comments: 0

Systematic yield issues are supplanting random defects as the dominant concern in semiconductor manufacturing at the most advanced process nodes, requiring more time, effort, and cost to achieve sufficient yield. Yield is the ultimate hush hush topic in semiconductor manufacturing, but it's also the most critical because it determines how many chips can be profitably sold. "At older nodes, b... » read more

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