tag: edge

Usage Models Driving Data Center Architecture Changes
By Ann Mutschler - 11 Feb, 2021 - Comments: 0

Data center architectures are undergoing a significant change, fueled by more data and much greater usage from remote locations. Part of this shift involves the need to move some processing closer to the various memory hierarchies, from SRAM to DRAM to storage. There is more data to process, and it takes less energy and time to process that data in place. But workloads also are being distrib... » read more

Powering The Edge: Driving Optimal Performance With Ethos-N77 Processor
By Arm - 10 Feb, 2021 - 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 read more. » read more

Data Overload In The Data Center
By Ed Sperling - 25 Jan, 2021 - Comments: 0

Dealing with increasing volumes of data inside of data centers requires an understanding of architectures, the flow of data between memory and processors, bandwidth, cache coherency and new memory types and interfaces. Gary Ruggles, senior product marketing manager at Synopsys, talks about how these systems are being revamped to improve performance and reduce power. » read more

Hidden Costs In Faster, Low-Power AI Systems
By Ed Sperling - 20 Jan, 2021 - Comments: 1

Chipmakers are building orders of magnitude better performance and energy efficiency into smart devices, but to achieve those goals they also are making tradeoffs that will have far-reaching, long-lasting, and in some cases unknown impacts. Much of this activity is a direct result of pushing intelligence out to the edge, where it is needed to process, sort, and manage massive increases in da... » read more

Power Models For Machine Learning
By Brian Bailey - 14 Dec, 2020 - Comments: 1

AI and machine learning are being designed into just about everything, but the chip industry lacks sufficient tools to gauge how much power and energy an algorithm is using when it runs on a particular hardware platform. The missing information is a serious limiter for energy-sensitive devices. As the old maxim goes, you can't optimize what you can't measure. Today, the focus is on functiona... » 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

The Cyber-Industrial Revolution
By Ed Sperling - 07 Dec, 2020 - Comments: 0

Semiconductors won't save the world, but they certainly will help. In fact, it's arguable whether any significant progress will be made on such issues as global warming or future medical breakthroughs without the aid of ICs. After decades of struggling just to get chips to work at each new process node, the semiconductor industry is moving into a new phase. Processing is now almost ubiquitou... » read more

Transforming Vision Inspection With Machine Learning
By Optimal Plus - 07 Dec, 2020 - Comments: 0

How auto-manufacturers can apply ML & AI algorithms to enhance image analytics on their factory floor and to ensure higher product quality? Discover the next generation visual inspection in our new case study. In this case study , you will learn about: Current limitations of image inspection in the manufacturing industry. The O+ end-to-end solution, which brings machine learning and... » read more

Edge Inference Applications And Market Segmentation
By Geoff Tate - 03 Dec, 2020 - Comments: 0

Until recently, most AI was in data centers/cloud and most of that was training. Things are changing quickly. Projections are AI sales will grow rapidly to tens of billions of dollars by the mid 2020s, with most of the growth in edge AI inference. Data center/cloud vs. edge inference: What’s the difference? The data center/cloud is where inference started on Xeons. To gain efficiency, much ... » read more

Week In Review: Auto, Security, Pervasive Computing
By Susan Rambo - 27 Nov, 2020 - Comments: 0

Automotive/Mobility China may act to rein in its EV market, according a story in Nikkei Asia. The National Development and Reform Commission in China asked for investment and production plans for EV projects over the last five years, which is signal to some industry insiders that the government may regulate some of the industry. Softbank and carmaker Subaru completed a test that used a 5G n... » read more

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