tag: machine learning

Hardware Fuzzer Utilizing LLMs
By Technical Paper Link - 12 Apr, 2024 - Comments: 0

A new technical paper titled "Beyond Random Inputs: A Novel ML-Based Hardware Fuzzing" was published by researchers at TU Darmstadt and Texas A&M University. Abstract "Modern computing systems heavily rely on hardware as the root of trust. However, their increasing complexity has given rise to security-critical vulnerabilities that cross-layer at-tacks can exploit. Traditional hardware ... » read more

High-NA EUVL: Automated Defect Inspection Based on SEMI-SuperYOLO-NAS
By Technical Paper Link - 10 Apr, 2024 - Comments: 0

A new technical paper titled "Towards Improved Semiconductor Defect Inspection for high-NA EUVL based on SEMI-SuperYOLO-NAS" was published by researchers at KU Leuven, imec, Ghent University, and SCREEN SPE. Abstract "Due to potential pitch reduction, the semiconductor industry is adopting High-NA EUVL technology. However, its low depth of focus presents challenges for High Volume Manufac... » read more

New Strategies For Interpreting Data Variability
By Gregory Haley - 09 Apr, 2024 - Comments: 0

Every measurement counts at the nanoscopic scale of modern semiconductor processes, but with each new process node the number of measurements and the need for accuracy escalate dramatically. Petabytes of new data are being generated and used in every aspect of the manufacturing process for informed decision-making, process optimization, and the continuous pursuit of quality and yield. Most f... » read more

Faster And Better Floorplanning With ML-Based Macro Placement
By Synopsys - 03 Apr, 2024 - Comments: 0

The chips contained in today’s consumer and commercial electronic products are staggering in size and complexity. The largest devices include central processing units (CPUs), graphics processing units (GPUs), and system-on-chip (SoC) devices that integrate many functions on a single die. Additionally, chips are expanding beyond their traditional borders with multi-die approaches such as 2.5DI... » read more

Ultimate Guide To Machine Learning For Embedded Systems
By Renesas - 03 Apr, 2024 - Comments: 0

Machine learning is a subfield of artificial intelligence which gives computers an ability to learn from data in an iterative manner using different techniques. Our aim here being to learn and predict from data. This is a big diversion from other fields which poses the limitation of programming instructions instead of learning from them. Machine learning in embedded systems specifically target ... » read more

Cadence Cerebrus In SaaS And Imagination Technologies Case Study
By Cadence - 27 Mar, 2024 - Comments: 0

Artificial Intelligence (AI) has made noteworthy progress and is now ready and available for electronic design automation. The Cadence Cerebrus Intelligent Chip Explorer utilizes AI—specifically, reinforcement machine learning (ML) technology—combined with the industry-leading Cadence digital full flow to deliver better power, performance, and area (PPA) more quickly. However, this highl... » read more

Transformer Model Based Clustering Methodology For Standard Cell Layout Automation (Nvidia)
By Technical Paper Link - 19 Mar, 2024 - Comments: 0

A new technical paper titled "Novel Transformer Model Based Clustering Method for Standard Cell Design Automation" was published by researchers at Nvidia. Abstract "Standard cells are essential components of modern digital circuit designs. With process technologies advancing beyond 5nm, more routability issues have arisen due to the decreasing number of routing tracks (RTs), increasing numb... » read more

Embrace The New!
By Steve Roddy - 14 Mar, 2024 - Comments: 0

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

A Hypermultiplexed Integrated Tensor Optical Processor (USC, MIT et al.)
By Technical Paper Link - 05 Mar, 2024 - Comments: 0

A technical paper titled “Hypermultiplexed Integrated Tensor Optical Processor” was published by researchers at the University of Southern California, Massachusetts Institute of Technology (MIT), City University of Hong Kong, and NTT Research. Abstract: "The escalating data volume and complexity resulting from the rapid expansion of artificial intelligence (AI), internet of things (IoT) a... » read more

Thanks For The Memories!
By Steve Roddy - 15 Feb, 2024 - Comments: 0

“I want to maximize the MAC count in my AI/ML accelerator block because the TOPs rating is what sells, but I need to cut back on memory to save cost,” said no successful chip designer, ever. Emphasis on “successful” in the above quote. It’s not a purely hypothetical quotation. We’ve heard it many times. Chip architects — or their marketing teams — try to squeeze as much brag-... » read more

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