tag: machine learning

Accelerating AI And ML Applications With PCIe 5
By Suresh Andani - 16 Jan, 2020 - Comments: 0

The rapid adoption of sophisticated artificial intelligence/machine learning (AI/ML) applications and the shift to cloud-based workloads has significantly increased network traffic in recent years. Historically, the intensive use of virtualization ensured that server compute capacity adequately met the need of heavy workloads. This was achieved by dividing or partitioning a single (physical) se... » read more

Uses And Limitations Of AI In Chip Design
By Ed Sperling - 15 Jan, 2020 - Comments: 0

Raik Brinkmann, president and CEO of OneSpin Solutions, sat down with Semiconductor Engineering to talk about AI changes and challenges, new opportunities for using existing technology to improve AI, and vice versa. What follows are excerpts of that conversation. SE: What's changing in AI? Brinkmann: There are a couple of big changes underway. One involves AI in functional safety, where y... » read more

Big Growth Areas: Connectivity, AI, Reliability
By Brian Bailey - 14 Jan, 2020 - Comments: 0

Connectivity and artificial intelligence (AI) will be the biggest drivers for 2020, with an emphasis on improved reliability across all areas. New standards, new applications, and new pressures being placed on old technology will created boundless opportunities for those ready to fill the need. Of course, there will also be a lot of carnage along the way, and we can expect to see a lot of that ... » read more

Bridging Math And Engineering In ML
By Ed Sperling - 08 Jan, 2020 - Comments: 0

Steve Roddy, vice president of products for Arm’s Machine Learning Group, examines the intersection of high-level mathematics in the data science used in machine learning within area, speed, and power limitations, and how to bring these two worlds together with the least amount of disruption. » read more

CEO Outlook: 2020 Vision
By Ed Sperling - 06 Jan, 2020 - Comments: 0

The start of 2020 is looking very different than the start of 2019. Markets that looked hazy at the start of 2019, such as 5G, are suddenly very much in focus. The glut of memory chips that dragged down the overall chip industry in 2019 has subsided. And a finely tuned supply chain that took decades to develop is splintering. A survey of CEOs from across the industry points to several common... » read more

Testing Autonomous Vehicles
By Ed Sperling - 16 Dec, 2019 - Comments: 0

Jeff Phillips, head of automotive marketing at National Instruments, talks about how to ensure that automotive systems are reliable and safe, how test needs to shift to adapt to continual updates and changes, and why this is particularly challenging in a world where there is no known right answer. » read more

How To Ensure Reliability
By Ed Sperling - 13 Dec, 2019 - Comments: 0

Michael Schuldenfrei, corporate technology fellow at OptimalPlus, talks about how to measure quality, why it’s essential to understand all of the possible variables in the testing process, and why outliers are no longer considered sufficient to ensure reliability. » read more

Into The Cold And Darkness
By Ed Sperling - 12 Dec, 2019 - Comments: 1

The need for speed is limitless. There is far more data to process, and there is competition on a global scale to process it fastest and most efficiently. But how to achieve future revs of improvements will begin to look very different from the past. For one thing, the new criteria for that speed are frequently tied to a fixed or shrinking power budget. This is why many benchmarks these days... » read more

Optimizing Power And Performance For Machine Learning At The Edge
By Mike Fingeroff - 12 Dec, 2019 - Comments: 0

While machine learning (ML) algorithms are popular for running on enterprise Cloud systems for training neural networks, AI/ML chipsets for edge devices are growing at a triple digit rate, according to Tractica “Deep Learning Chipsets” (Figure 1). Edge devices include automobiles, drones, and mobile devices that are all employing AI/ML to provide valuable functionality. Figure 1: Marke... » read more

Defining And Improving AI Performance
By Brian Bailey - 12 Dec, 2019 - Comments: 0

Many companies are developing AI chips, both for training and for inference. Although getting the required functionality is important, many solutions will be judged by their performance characteristics. Performance can be measured in different ways, such as number of inferences per second or per watt. These figures are dependent on a lot of factors, not just the hardware architecture. The optim... » read more

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