tag: AI

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

Getting Better Edge Performance & Efficiency From Acceleration-Aware ML Model Design
By Vlad Bronstein - 04 Nov, 2021 - Comments: 0

The advent of machine learning techniques has benefited greatly from the use of acceleration technology such as GPUs, TPUs and FPGAs. Indeed, without the use of acceleration technology, it’s likely that machine learning would have remained in the province of academia and not had the impact that it is having in our world today. Clearly, machine learning has become an important tool for solving... » read more

Easier And Faster Ways To Train AI
By Bryon Moyer - 04 Nov, 2021 - Comments: 0

Training an AI model takes an extraordinary amount of effort and data. Leveraging existing training can save time and money, accelerating the release of new products that use the model. But there are a few ways this can be done, most notably through transfer and incremental learning, and each of them has its applications and tradeoffs. Transfer learning and incremental learning both take pre... » read more

What’s Missing For Designing Chips At The System Level
By Ed Sperling - 01 Nov, 2021 - Comments: 0

Semiconductor Engineering sat down to talk about design challenges in advanced packages and nodes with John Lee, vice president and general manager for semiconductors at Ansys; Shankar Krishnamoorthy, general manager of Synopsys' Design Group; Simon Burke, distinguished engineer at Xilinx; and Andrew Kahng, professor of CSE and ECE at UC San Diego. This discussion was held at the Ansys IDEAS co... » read more

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