AI At The Edge: Optimizing AI Algorithms Without Sacrificing Accuracy

By Ron Lowman - 07 Jul, 2022 - Comments: 0

The ultimate measure of success for AI will be how much it increases productivity in our daily lives. However, the industry has huge challenges in evaluating progress. The vast number of AI applications is in constant churn: finding the right algorithm, optimizing the algorithm, and finding the right tools. In addition, complex hardware engineering is rapidly being updated with many different s... » read more

Mapping Transformation Enabled High-Performance and Low-Energy Memristor-Based DNNs

By Technical Paper Link - 14 Mar, 2022 - Comments: 0

Abstract: "When deep neural network (DNN) is extensively utilized for edge AI (Artificial Intelligence), for example, the Internet of things (IoT) and autonomous vehicles, it makes CMOS (Complementary Metal Oxide Semiconductor)-based conventional computers suffer from overly large computing loads. Memristor-based devices are emerging as an option to conduct computing in memory for DNNs to make... » read more

Seven Hardware Advances We Need to Enable The AI Revolution

By Remy Pottier - 10 Mar, 2022 - Comments: 1

The potential, positive impact AI will have on society at large is impossible to overestimate. Pervasive AI, however, remains a challenge. Training algorithms can take inordinate amounts of power, time, and computing capacity. Inference will also become more taxing with applications such as medical imaging and robotics. Applied Materials estimates that AI could consume up to 25% of global elect... » read more

Flexible USB4-Based Interface IP Solution For AI At The Edge

By Synopsys - 21 Dec, 2021 - Comments: 0

Consumers have become accustomed to smart devices that are powered by advances in artificial intelligence (AI). To expand the devices’ total addressable market, innovative device designers build edge AI accelerators and edge AI SoCs that support multiple use cases and integration options. This white paper describes a flexible USB4-based IP solution for edge AI accelerators and SoCs. The IP so... » read more

Deploying Artificial Intelligence At The Edge

By Pushkar Apte - 16 Sep, 2021 - Comments: 0

By Pushkar Apte and Tom Salmon Rapid advances in artificial intelligence (AI) have made this technology important for many industries, including finance, energy, healthcare, and microelectronics. AI is driving a multi-trillion-dollar global market while helping to solve some tough societal problems such as tracking the current pandemic and predicting the severity of climate-driven events lik... » read more

Challenges In Developing A New Inferencing Chip

By Ed Sperling - 01 Jul, 2021 - Comments: 0

Cheng Wang, co-founder and senior vice president of software and engineering at Flex Logix, sat down with Semiconductor Engineering to explain the process of bringing an inferencing accelerator chip to market, from bring-up, programming and partitioning to tradeoffs involving speed and customization. SE: Edge inferencing chips are just starting to come to market. What challenges di... » read more

Kria K26 SOM: The Ideal Platform For Vision AI At The Edge

By Xilinx - 12 May, 2021 - Comments: 0

With various advancements in artificial intelligence (AI) and machine learning (ML) algorithms, many high-compute applications are now getting deployed on edge devices. So, there is a need for an efficient hardware that can execute complex algorithms efficiently as well as adapt to rapid enhancements in this technology. Xilinx's Kria K26 SOM is designed to address the requirements of executing ... » read more

Powering The Edge: Driving Optimal Performance With Ethos-N77 Processor

By Arm - 09 Dec, 2020 - Comments: 0

Repurposing a CPU, GPU, or DSP is an easy way to add ML capabilities to an edge device. However, where responsiveness or power efficiency is critical, a dedicated Neural Processing Unit (NPU) may be the best solution. In this paper, we describe how the Arm Ethos-N77 NPU delivers optimal performance. Click here to immediately download the paper. » read more

Week In Review: Auto, Security, Pervasive Computing

By Susan Rambo - 30 Oct, 2020 - Comments: 0

Automotive Synopsys added support for Infineon's automotive AI chip, the AURIX TC4xx 32-bit microcontroller with parallel processing unit. Dialog Semiconductor announced automotive qualification for its DA7280 high-definition haptic driver. The company Alps Alpine is using the DA7280 in Alps Alpine Heavy, the latest version of its HAPTIC Reactor Linear Resonant Actuators (LRAs). Bosch, M... » read more

The Emergence Of Hardware As A Key Enabler For The Age Of Artificial Intelligence

By Stelios Diamantidis - 13 Aug, 2020 - Comments: 0

Over the past few decades, software has been the engine of innovation for countless applications. From PCs to mobile phones, well-defined hardware platforms and instruction set architectures (ISA) have enabled many important advancements across vertical markets. The emergence of abundant-data computing is changing the software-hardware balance in a dramatic way. Diverse AI applications in fa... » read more

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tag: edge AI

AI At The Edge: Optimizing AI Algorithms Without Sacrificing Accuracy

Mapping Transformation Enabled High-Performance and Low-Energy Memristor-Based DNNs

Seven Hardware Advances We Need to Enable The AI Revolution

Flexible USB4-Based Interface IP Solution For AI At The Edge

Deploying Artificial Intelligence At The Edge

Challenges In Developing A New Inferencing Chip

Kria K26 SOM: The Ideal Platform For Vision AI At The Edge

Powering The Edge: Driving Optimal Performance With Ethos-N77 Processor

Week In Review: Auto, Security, Pervasive Computing

The Emergence Of Hardware As A Key Enabler For The Age Of Artificial Intelligence

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