tag: neural networks

Future-proofing AI Models
By Ann Mutschler - 21 May, 2025 - Comments: 0

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

Energy-Aware DL: The Interplay Between NN Efficiency And Hardware Constraints (Imperial College London, Cambridge)
By Technical Paper Link - 20 May, 2025 - Comments: 0

A new technical paper titled "Energy-Aware Deep Learning on Resource-Constrained Hardware" was published by researchers at Imperial College London and University of Cambridge. Abstract "The use of deep learning (DL) on Internet of Things (IoT) and mobile devices offers numerous advantages over cloud-based processing. However, such devices face substantial energy constraints to prolong batte... » read more

AI Accelerators Moving Out From Data Centers
By Ann Mutschler - 15 May, 2025 - Comments: 0

Experts At The Table: The explosion in AI data is driving chipmakers to look beyond a single planar SoC. Semiconductor Engineering sat down to discuss the need for more computing and the expanding role of chiplets with Marc Meunier, director of ecosystem development at Arm; Jason Lawley, director of product marketing for AI IP at Cadence; Paul Karazuba, vice president of marketing at Expedera; ... » read more

Research Bits: April 22
By Jesse Allen - 22 Apr, 2025 - Comments: 0

PIC heterogeneous integration Researchers from Hewlett Packard Labs, Indian Institutes of Technology Madras, Microsoft Research, and University of Michigan built an AI acceleration platform based on heterogeneously integrated photonic ICs. The PIC combines silicon photonics along with III-V compound semiconductors that functionally integrate lasers and optical amplifiers to reduce optical l... » read more

Implementing AI Activation Functions
By Bryon Moyer - 10 Apr, 2025 - Comments: 1

Activation functions play a critical role in AI inference, helping to ferret out nonlinear behaviors in AI models. This makes them an integral part of any neural network, but nonlinear functions can be fussy to build in silicon. Is it better to have a CPU calculate them? Should hardware function units be laid down to execute them? Or would a lookup table (LUT) suffice? Most architectures inc... » read more

Physics Simulation With Graph Neural Networks Targeting Mobile
By Máté Stodulka - 13 Mar, 2025 - Comments: 0

By Máté Stodulka and Tomas Zilhao Borges The demand for immersive, realistic graphics in mobile gaming and AR or VR is pushing the limits of mobile hardware. Achieving lifelike simulations of fluids, cloth, and other materials historically requires intensive mathematical computations. While these traditional methods yield highly accurate results, they have been too resource-heavy to run re... » read more

The Optical Implementation of Backpropagation (Oxford, Lumai)
By Technical Paper Link - 07 Mar, 2025 - Comments: 0

A technical paper titled "Training neural networks with end-to-end optical backpropagation" was published by researchers at University of Oxford and Lumai Ltd. Abstract "Optics is an exciting route for the next generation of computing hardware for machine learning, promising several orders of magnitude enhancement in both computational speed and energy efficiency. However, reaching the full... » read more

What Scares Chip Engineers About Generative AI
By Adam Kovac - 26 Feb, 2025 - Comments: 0

Experts At The Table: LLMs and other generative AI programs are a long way away from being able to design entire chips on their own from scratch, but the emergence of the tech has still raised some genuine concerns. Semiconductor Engineering sat down with a panel of experts, which included Rod Metcalfe, product management group director at Cadence; Syrus Ziai, vice-president of engineering at E... » read more

Real-Time Low Light Video Enhancement Using Neural Networks On Mobile
By Ayaan Masood - 17 Oct, 2024 - Comments: 0

Video conferencing is a ubiquitous tool for communication, especially for remote work and social interactions. However, it is not always a straightforward plug and play experience, as adjustments may be needed to ensure a good audio and video setup. Lighting is one such factor that can be tricky to get right. A nicely illuminated video feed looks presentable in a meeting, but on the other hand,... » read more

Characteristics and Potential HW Architectures for Neuro-Symbolic AI
By Technical Paper Link - 23 Sep, 2024 - Comments: 0

A new technical paper titled "Towards Efficient Neuro-Symbolic AI: From Workload Characterization to Hardware Architecture" was published by researchers at Georgia Tech, UC Berkeley, and IBM Research. Abstract: "The remarkable advancements in artificial intelligence (AI), primarily driven by deep neural networks, are facing challenges surrounding unsustainable computational trajectories, li... » read more

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