tag: AI

Will Markets For ML Models Materialize?
By Bryon Moyer - 02 Dec, 2021 - Comments: 0

Developers are spending increasing amounts of time and effort in creating machine-learning (ML) models for use in a wide variety of applications. While this will continue as the market matures, at some point some of these efforts might be seen as reinventing models over and over. Will developers of successful models ever have a marketplace in which they can sell those models as IP to other d... » read more

Gaps In The AI Debug Process
By Brian Bailey - 23 Nov, 2021 - Comments: 0

When an AI algorithm is deployed in the field and gives an unexpected result, it's often not clear whether that result is correct. So what happened? Was it wrong? And if so, what caused the error? These are often not simple questions to answer. Moreover, as with all verification problems, the only way to get to the root cause is to break the problem down into manageable pieces. The semico... » read more

Raising The Bar With The Next Generation Of AI For Chip Design
By Synopsys - 22 Nov, 2021 - Comments: 0

The semiconductor industry is enjoying renewed growth despite chip shortages plaguing everything from cars to kitchen appliances. But while the chips themselves continue to get faster and smarter, the chip design process itself hasn’t changed that much in 20+ years. It typically takes 2-3 years to design a chip with a large engineering team and tens or hundreds of millions of dollars to get a... » read more

Absence of Barren Plateaus in Quantum Convolutional Neural Networks
By Technical Paper Link - 18 Nov, 2021 - Comments: 0

Abstract:  Quantum neural networks (QNNs) have generated excitement around the possibility of efficiently analyzing quantum data. But this excitement has been tempered by the existence of exponentially vanishing gradients, known as barren plateau landscapes, for many QNN architectures. Recently, quantum convolutional neural networks (QCNNs) have been proposed, involving a sequence of convol... » read more

A Broad Look Inside Advanced Packaging
By Mark LaPedus - 18 Nov, 2021 - Comments: 0

Choon Lee, chief technology officer of JCET, sat down with Semiconductor Engineering to talk about the semiconductor market, Moore’s Law, chiplets, fan-out packaging, and manufacturing issues. What follows are excerpts of that discussion. SE: Where are we in the semiconductor cycle right now? Lee: If you look at 2020, it was around 10% growth in the overall semiconductor industry. ... » read more

AI/ML Workloads Need Extra Security
By Bryon Moyer - 15 Nov, 2021 - Comments: 0

The need for security is pervading all electronic systems. But given the growth in data-center machine-learning computing, which deals with extremely valuable data, some companies are paying particular attention to handling that data securely. All of the usual data-center security solutions must be brought to bear, but extra effort is needed to ensure that models and data sets are protected ... » read more

HBM2E Raises The Bar For Memory Bandwidth
By Rambus - 10 Nov, 2021 - Comments: 0

AI/ML training capabilities are growing at a rate of 10X per year driving rapid improvements in every aspect of computing hardware and software. HBM2E memory is the ideal solution for the high bandwidth requirements of AI/ML training, but entails additional design considerations given its 2.5D architecture. Designers can realize the full benefits of HBM2E memory with the silicon-proven memory s... » read more

A graph placement methodology for fast chip design
By Technical Paper Link - 09 Nov, 2021 - Comments: 0

Abstract "Chip floorplanning is the engineering task of designing the physical layout of a computer chip. Despite five decades of research1, chip floorplanning has defied automation, requiring months of intense effort by physical design engineers to produce manufacturable layouts. Here we present a deep reinforcement learning approach to chip floorplanning. In under six hours, our method autom... » read more

Enablers And Barriers For Connecting Diverse Data
By Anne Meixner - 09 Nov, 2021 - Comments: 0

More data is being collected at every step of the manufacturing process, raising the possibility of combining data in new ways to solve engineering problems. But this is far from simple, and combining results is not always possible. The semiconductor industry’s thirst for data has created oceans of it from the manufacturing process. In addition, semiconductor designs large and small now ha... » read more

Solving Real World AI Productization Challenges With Adaptive Computing
By Nick Ni - 08 Nov, 2021 - Comments: 0

The field of artificial intelligence (AI) moves swiftly, with the pace of innovation only accelerating. While the software industry has been successful in deploying AI in production, the hardware industry – including automotive, industrial, and smart retail – is still in its infancy in terms of AI productization. Major gaps still exist that hinder AI algorithm proof-of-concepts (PoC) from b... » read more

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