Partitioning Processors For AI Workloads


Partitioning in complex chips is beginning to resemble a high-stakes guessing game, where choices need to extrapolate from what is known today to what is expected by the time a chip finally ships. Partitioning of workloads used to be a straightforward task, although not necessarily a simple one. It depended on how a device was expected to be used, the various compute, storage and data paths ... » read more

AI Transformer Models Enable Machine Vision Object Detection


The object detection required for machine vision applications such as autonomous driving, smart manufacturing, and surveillance applications depends on AI modeling. The goal now is to improve the models and simplify their development. Over the years, many AI models have been introduced, including YOLO, Faster R-CNN, Mask R-CNN, RetinaNet, and others, to detect images or video signals, interp... » read more

Designing Crash-Proof Autonomous Vehicles


Autonomous vehicles keep crashing into things, even though ADAS technology promises to make driving safer because machines can think and react faster than human drivers. Humans rely on seeing and hearing to assess driving conditions. When drivers detect objects in front of the vehicle, the automatic reaction is to slam on the brakes or swerve to avoid them. Quite often drivers cannot react q... » read more

IC Security Issues Grow, Solutions Lag


Experts at the Table: Semiconductor Engineering sat down to talk about the growing chip security threat and what's being done to mitigate it, with Mike Borza, Synopsys scientist; John Hallman, product manager for trust and security at Siemens EDA; Pete Hardee, group director for product management at Cadence; Paul Karazuba, vice president of marketing at Expedera; and Dave Kelf, CEO of Breker V... » read more

More Efficient Matrix-Multiplication Algorithms with Reinforcement Learning (DeepMind)


A new research paper titled "Discovering faster matrix multiplication algorithms with reinforcement learning" was published by researchers at DeepMind. "Here we report a deep reinforcement learning approach based on AlphaZero for discovering efficient and provably correct algorithms for the multiplication of arbitrary matrices," states the paper. Find the technical paper link here. Publis... » read more

Architecting Faster Computers


To create faster computers, the industry must take a major step back and re-examine choices that were made half a century ago. One of the most likely approaches involves dropping demands for determinism, and this is being attempted in several different forms. Since the establishment of the von Neumann architecture for computers, small, incremental improvements have been made to architectures... » read more

Improving Medical Image Processing With AI


Machine learning is being integrated with medical image processing, one of the most useful technologies for medical diagnosis and surgery, greatly expanding the amount of useful information that can be gleaned from scan or MRI. For the most part, ML is being used to augment manual processes that medical personnel use today. While the goal is to automate many of these functions, it's not clea... » read more

EDA Vendors Widen Use Of AI


EDA vendors are widening the use of AI and machine learning to incorporate multiple tools, providing continuity and access to consistent data at multiple points in the semiconductor design flow. While gaps remain, early results from a number of EDA tools providers point to significant improvements in performance, power, and time to market. AI/ML has been deployed for some time in EDA. Still,... » read more

Software-Hardware Co-Design Becomes Real


For the past 20 years, the industry has sought to deploy hardware/software co-design concepts. While it is making progress, software/hardware co-design appears to have a much brighter future. In order to understand the distinction between the two approaches, it is important to define some of the basics. Hardware/software co-design is essentially a bottom-up process, where hardware is deve... » read more

Monitoring Performance From Inside A Chip


Deep data, which is generated inside the chip rather than externally, is becoming more critical at each new process node and in advanced packages. Uzi Baruch, chief strategy officer at proteanTecs, talks with Semiconductor Engineering about using that data to identify potential problems before they result in failures in the field, and why it's essential to monitor these devices throughout their... » read more

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