Understanding SLAM (Simultaneous Localization And Mapping)

By Ed Sperling - 19 Feb, 2020 - Comments: 0

Amol Borkar, senior product manager for AI and computer vision at Cadence, talks with Semiconductor Engineering about mapping and tracking the movement of an object in a scene, how to identify key corners in a frame, how probabilities of accuracy fit into the picture, how noise can affect that, and how to improve the performance and reduce power in these systems. » read more

Week In Review: IoT, Security, Autos

By Susan Rambo - 10 Jan, 2020 - Comments: 0

Internet of Things Sensors that see in the dark, look deep into our faces and hear the impossible, were all part of ams’ CES lineup this week. ams announced that it has designed an advanced spectral ambient light sensor (ALS) for high-end mobile phone cameras. The ALS, called the AS7350, identifies the light source and makes an accurate white balance under low-light and other non-ideal condi... » read more

Fixed and Floating FMCW Radar Signal Processing with Tensilica DSPs

By Cadence - 04 Dec, 2019 - Comments: 0

Automotive advanced driver assistance system (ADAS) applications increasingly demand radar modules with better capability and performance. These applications require sophisticated radar processing algorithms and powerful digital signal processors (DSPs) to run them. Because these embedded systems have limited power and cost budgets, the DSP’s instruction set architecture (ISA) needs to be eff... » read more

Week in Review: IoT, Security, Autos

By Jeff Dorsch - 25 Oct, 2019 - Comments: 0

Products/Services Rambus reports completing the sale of its Payments and Ticketing businesses to Visa for $75 million in cash. “With 30 years of experience pushing the envelope in semiconductor design, we look toward a future of continued innovation to carry on our mission of making data faster and safer,” Rambus President and CEO Luc Seraphin said in a statement. “Completing this transa... » read more

Making Sense Of ML Metrics

By Ed Sperling - 16 Oct, 2019 - Comments: 0

Steve Roddy, vice president of products for Arm’s Machine Learning Group, talks with Semiconductor Engineering about what different metrics actually mean, and why they can vary by individual applications and use cases. » read more

High-Performance DSP And Control Processing For Complex 5G Requirements

By Graham Wilson - 12 Sep, 2019 - Comments: 0

In the early 2000s, digital signal processors (DSP) were simple in architecture and limited in performance, but complex in programming. However, they evolved to meet of the increased performance requirements of 3G cellular baseband modem applications. A typical 3G modem system would have a single DSP optimized for dual/quad SIMD MAC performance with basic DSP filter instructions like Fast Fouri... » read more

Why Scaling Must Continue

By Ed Sperling - 15 Aug, 2019 - Comments: 3

The entire semiconductor industry has come to the realization that the economics of scaling logic are gone. By any metric—price per transistor, price per watt, price per unit area of silicon—the economics are no longer in the plus column. So why continue? The answer is more complicated than it first appears. This isn't just about inertia and continuing to miniaturize what was proven in t... » read more

Powering The Edge: Driving Optimal Performance With the Arm ML Processor

By Arm - 07 Aug, 2019 - Comments: 0

On-device machine learning (ML) processing is already happening in more than 4 billion smart phones. As the adoption of connected devices continues to grow exponentially, the resulting data explosion means cloud processing could soon become an expensive and high-latency luxury. The Arm ML processor is defining the future of ML inference at the edge, allowing smart devices to make independent... » read more

Using Compression For High-Bandwidth Video

By Ed Sperling - 01 Aug, 2019 - Comments: 0

Malte Doerper, senior manager for product management at Synopsys, explains how to improve bandwidth and reduce latency in video without changing out the existing infrastructure through compression, but unlike previous versions of compression there is no significant loss of quality. This approach reduces power, area and heat, as well. » read more

Say Welcome to the Machine: Low-Power Machine Learning for Smart IoT Applications

By Synopsys - 24 Jul, 2019 - Comments: 0

By Pieter van der Wolf, Principal R&D Engineer, Synopsys Inc. and Dmitry Zakharov, Senior Software Engineer, Synopsys Inc Smart IoT devices that interact intelligently with their users are appearing in many application areas. Increasingly, these devices apply machine learning technology for processing captured sensor data, so that smart actions can be taken based on recognized patterns. ... » read more

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Knowledge Centers
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