AI Drives IC Design Shifts At The Edge

By Adam Kovac and Ed Sperling - 07 Nov, 2024 - Comments: 0

The increasing adoption of AI in edge devices, coupled with a growing demand for new features, is forcing chipmakers to rethink when and where data gets processed, what kind of processors to use, and how to build enough flexibility into systems to span multiple markets. Unlike in the cloud, where the solution generally involves nearly unlimited resources, computing at the edge has sharp cons... » read more

Hardware Acceleration Approach for KAN Via Algorithm-Hardware Co-Design

By Technical Paper Link - 26 Sep, 2024 - Comments: 2

A new technical paper titled "Hardware Acceleration of Kolmogorov-Arnold Network (KAN) for Lightweight Edge Inference" was published by researchers at Georgia Tech, TSMC and National Tsing Hua University. Abstract "Recently, a novel model named Kolmogorov-Arnold Networks (KAN) has been proposed with the potential to achieve the functionality of traditional deep neural networks (DNNs) using ... » read more

Evolving Edge Computing And Harnessing Heterogeneity

By Alexandre Ferreira - 12 Sep, 2024 - Comments: 0

In the Evolving Edge Computing white paper, we highlighted 3 challenges to enable the Intelligent Edge, they are: Enabling hardware heterogeneity Removing development friction Ensuring security at scale This blog post examines the first in that list, heterogeneity. It will cover the ways in which heterogeneity appears, its effect on systems and some ideas for resolving its inher... » read more

A Software-First Mindset for Driving Efficiency and Sustainability for Industrial IoT

By Arm - 07 Aug, 2024 - Comments: 0

Schneider Electric, Arm, and system integrators Witekio and Capgemini have produced a software-defined platform for industrial automation and energy management. The platform uses cloud-native techniques to create a flexible, energy-efficient reference design that uses virtualization to enable real-time, mixed-criticality services at the embedded edge. Read more here. » read more

Survey of Energy Efficient PIM Processors

By Technical Paper Link - 01 Aug, 2024 - Comments: 0

A new technical paper titled "Survey of Deep Learning Accelerators for Edge and Emerging Computing" was published by researchers at University of Dayton and the Air Force Research Laboratory. Abstract "The unprecedented progress in artificial intelligence (AI), particularly in deep learning algorithms with ubiquitous internet connected smart devices, has created a high demand for AI compu... » read more

Simplifying AI Deployment from the Cloud to Edge and Endpoint

By Renesas - 31 Jul, 2024 - Comments: 0

Artificial Intelligence (AI) is transforming every aspect of life. It is enhancing quality in industrial applications, enabling smart home systems, monitoring our safety as we work and play. Advances in technology have allowed us to run complex machine learning algorithms to tackle unique problems allowing those to be implemented also on embedded devices used in our daily life in home and indus... » read more

On-Device Speaker Identification For Digital Television (DTV)

By Marcus Corbin - 18 Jul, 2024 - Comments: 0

In recent years, the way we interact with our TVs has changed. Multiple button presses to navigate an on-screen keyboard have been replaced with direct interaction through our voices. While this has resulted in significant improvements to the Digital Television (DTV) user experience, more can be done to provide immersive and engaging experiences. Imagine you say, “recommend me a film” or... » read more

Evolving Edge Computing

By Arm - 17 Jul, 2024 - Comments: 0

Edge computing is a term that has been in use for a long time. Throughout the industry, there are many references to edge and many pre-conceptions about what that might mean. The term ‘edge’ is typically used for devices that exist on the edge of a network and can cover a plethora of use cases, ranging from the router in your house, a smart video camera surveying a parking lot, to a control... » read more

Dedicated Approximate Computing Framework To Efficiently Compute PCs On Hardware

By Technical Paper Link - 20 Jun, 2024 - Comments: 0

A technical paper titled “On Hardware-efficient Inference in Probabilistic Circuits” was published by researchers at Aalto University and UCLouvain. Abstract: "Probabilistic circuits (PCs) offer a promising avenue to perform embedded reasoning under uncertainty. They support efficient and exact computation of various probabilistic inference tasks by design. Hence, hardware-efficient compu... » read more

MCU Changes At The Edge

By Ed Sperling - 03 Jun, 2024 - Comments: 0

Microcontrollers are becoming a key platform for processing machine learning at the edge due to two significant changes. First, they now can include multiple cores, including some for high performance and others for low power, as well as other specialized processing elements such as neural network accelerators. Second, machine learning algorithms have been pruned to the point where inferencing ... » read more

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Knowledge Centers
Entities, people and technologies explored

Shift Left Is The Tip Of The Iceberg

A transformative change is underway for semiconductor design and EDA. New languages, models, and abstractions will need to be created.

by Brian Bailey

Partitioning In The Chiplet Era

Understanding how chiplets interact under different workloads is critical to ensuring signal integrity and optimal performance in heterogeneous designs.

by Ann Mutschler

3.5D: The Great Compromise

Pros and cons of a middle-ground chiplet assembly that combines 2.5D and 3D-IC.

by Ed Sperling

AI’s Role In Chip Design Widens, Drawing In New Startups

Focus is on letting engineers do much more with the same or fewer resources — and less drudgery.

by Karen Heyman

Key Technologies To Extend EUV To 14 Angstroms

Alongside high-NA EUV will be better-performing photoresists, reduced roughness using passivation and etch, and lateral etching to reduce tip-to-tip dimensions.

by Laura Peters

Memory Fundamentals For Engineers

eBook: Nearly everything you need to know about memory, including detailed explanations of the different types of memory; how and where these are used today; what's changing, which memories are successful and which ones might be in the future; and the limitations of each memory type.

by The SE Staff

What Comes After HBM For Chiplets

The standard for high-bandwidth memory limits design freedom at many levels, but that is required for interoperability. What freedoms can be taken from other functions to make chiplets possible?