Optical Interconnectivity At 224 Gbps


AI is generating so much traffic that traditional copper-based approaches for moving data inside a chip, between chips, and between systems, are running out of steam. Just adding more channels is no longer viable. It requires more power to drive signals, and the distance those signals can travel without excessive loss is shrinking. Mike Klempa, product marketing specialist at Alphawave Semi, di... » read more

Inside Chips Podcast: May 27


Jo De Boeck, chief strategy officer and EVP at imec, talks with Semiconductor Engineering Technology Editor Gregory Haley about system technology co-optimization and the intersection of technology and AI. https://www.youtube.com/watch?v=XUgQPBIaDHQ » read more

Energy-Efficient Computing Systems For Sustainable AI


As artificial intelligence (AI) proliferates rapidly, AI models and datasets are also growing rapidly in size. This growth far outpaces performance improvement in hardware systems, and is increasing AI’s energy consumption unsustainably. To address these challenges and explore collaborative solutions, SEMI’s Smart Data-AI Initiative – as part of its Future of Computing focus – r... » read more

Future-proofing AI Models


Experts At The Table: Making sure AI accelerators can be updated for future requirements is becoming essential due to the rapid introduction of new models. Semiconductor Engineering sat down to discuss the challenges of future-proofing these designs with Marc Meunier, director of ecosystem development at Arm; Jason Lawley, director of product marketing for AI IP at Cadence; Paul Karazuba, vic... » read more

HBM4 Elevates AI Training Performance To New Heights


Generative and Agentic AI are pushing an extremely rapid evolution of computing technology. With leading-edge LLMs now in excess of a trillion parameters, training takes an enormous amount of computing capacity, and state-of-the-art training clusters can employ more than 100,000 GPUs. High Bandwidth Memory (HBM) provides the vast memory bandwidth and capacity needed for these demanding AI train... » read more

Trapped By Legacy


At Quadric, we do a lot of first-time introductory visits with prospective new customers. As a rapidly expanding processor IP licensing company that is starting to get noticed (even winning IP Product of the Year!) such meetings are part of the territory. Which means we hear a lot of similar-sounding questions from appropriately skeptical listeners who hear our story for the very first time. Th... » read more

Deploying PyTorch Models On Edge Devices


AI is being rapidly adopted in edge computing. As a result, it is increasingly important to deploy machine learning models on Arm edge devices. Arm-based processors are common in embedded systems because of their low power consumption and efficiency. This tutorial shows you how to deploy PyTorch models on Arm edge devices, such as the Raspberry Pi or NVIDIA Jetson Nano. Prerequisites Before y... » read more

High-Speed Test IO: Addressing High-Performance Data Transmission And Testing Needs For HPC & AI


By Lakshmi Jain and Wei-Yu Ma The AI and HPC industries are rapidly shifting toward chiplet-based designs to achieve unprecedented levels of performance, as traditional monolithic system-on-chip (SoC) architectures face scaling limitations. This transition is fueled by the rise of heterogeneous integration, which is driving innovation across the semiconductor sector. However, this advancemen... » read more

UALink: Powering The Future Of AI Compute


On April 25, the UALink Consortium officially released the UALink 200G 1.0 Specification, marking an important milestone with support from key hyperscalar market players. It enables a low-latency, high-bandwidth fabric that supports hundreds of accelerators in a pod and facilitates simple load-and-store semantics. Motivation behind UALink The rapid evolution of Artificial Intelligence (AI) an... » read more

Impact of AI On IP And Chip Design


By Global Semiconductor Alliance (GSA) In conjunction with the Global Semiconductor Alliance's IP Interest group, Expedera explores the impact of AI on intellectual property (IP) and Chip Design, providing comprehensive details and multifaceted data to cover all aspects of the semiconductor industry. It highlights AI growth trends, market predictions, and current silicon chip design innovati... » read more

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