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Maximizing Edge AI Performance


Inference of convolutional neural network models is algorithmically straightforward, but to get the fastest performance for your application there are a few pitfalls to keep in mind when deploying. A number of factors make efficient inference difficult, which we will first step through before diving into specific solutions to address and resolve each. By the end of this article, you will be arm... » read more

New Uses For AI


AI is being embedded into an increasing number of technologies that are commonly found inside most chips, and initial results show dramatic improvements in both power and performance. Unlike high-profile AI implementations, such as self-driving cars or natural language processing, much of this work flies well under the radar for most people. It generally takes the path of least disruption, b... » read more

The Best AI Edge Inference Benchmark


When evaluating the performance of an AI accelerator, there’s a range of methodologies available to you. In this article, we’ll discuss some of the different ways to structure your benchmark research before moving forward with an evaluation that directly runs your own model. Just like when buying a car, research will only get you so far before you need to get behind the wheel and give your ... » read more

Usage Models Driving Data Center Architecture Changes


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


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


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


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


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


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


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

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