tag: ML

Accelerating AI/ML Inferencing With GDDR6 DRAM
By Frank Ferro - 10 Jun, 2021 - Comments: 0

The origins of graphics double data rate (GDDR) memory can be traced to the rise of 3D gaming on PCs and consoles. The first graphics processing units (GPU) packed single data rate (SDR) and double data rate (DDR) DRAM – the same solution used for CPU main memory. As gaming evolved, the demand for higher frame rates at ever higher resolutions drove the need for a graphics-workload specific me... » read more

3 Technologies That Will Challenge Test
By Ed Sperling - 08 Jun, 2021 - Comments: 0

As chips are deployed in more complex systems and with new technologies, it's not clear exactly what chipmakers and systems vendors will be testing. The standard tests for voltage, temperature and electrical throughput still will be needed, of course. But that won't be sufficient to ensure that sensor fusion, machine learning, or millimeter wave 5/6G will be functioning properly. Each of tho... » read more

Scaling Simulation
By Brian Bailey - 27 May, 2021 - Comments: 1

Without functional simulation the semiconductor industry would not be where it is today, but some people in the industry contend it hasn't received the attention and research it deserves, causing a stagnation in performance. Others disagree, noting that design sizes have increased by orders of magnitude while design times have shrunk, pointing to simulation remaining a suitable tool for the job... » 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

Securing AI/ML With A Hardware Root Of Trust
By Thierry Kouthon - 06 May, 2021 - Comments: 0

AI/ML (Artificial Intelligence/Machine Learning) is now pervasive across all industries. It contributes to rationalizing and harnessing the enormous amount of information made available by the current massive wave of digitization. Digitization is transforming how business is run and how value is produced using digital technologies. Data, the raw material of AI/ML and deep learning algorithms, i... » read more

New Uses For AI
By Ed Sperling - 01 Apr, 2021 - Comments: 0

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

How To Measure ML Model Accuracy
By Bryon Moyer - 01 Apr, 2021 - Comments: 0

Machine learning (ML) is about making predictions about new data based on old data. The quality of any machine-learning algorithm is ultimately determined by the quality of those predictions. However, there is no one universal way to measure that quality across all ML applications, and that has broad implications for the value and usefulness of machine learning. “Every industry, every d... » read more

The Other Side Of AI System Reliability
By Ed Sperling - 09 Mar, 2021 - Comments: 0

Adding intelligence into pervasive electronics will have consequences, but not necessarily what most people expect. Nearly everything electronic these days has some sort of "smart" functionality built in or added on. This can be as simple as a smoke alarm that alerts you when the batteries are running low, a home assistant that learns your schedule and dials the thermostat up or down, or a r... » read more

Making Sure AI/ML Works In Test Systems
By Susan Rambo - 09 Mar, 2021 - Comments: 0

Artificial intelligence/machine learning is being utilized increasingly to find patterns and outlier data in chip manufacturing and test, improving the overall yield and reliability of end devices. But there are too many variables and unknowns to reliably predict how a chip will behave in the field using just AI. Today, every AI use case — whether a self-driving car or an industrial sortin... » read more

Firmware Skills Shortage
By Brian Bailey - 25 Feb, 2021 - Comments: 0

Good hardware without good software is a waste of silicon, but with so many new processors and accelerator architectures being created, and so many new skills required, companies are finding it hard to hire enough engineers with low-level software expertise to satisfy the demand. Writing compilers, mappers and optimization software does not have the same level of pizazz as developing new AI ... » read more

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