tag: AI

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

The Best AI Edge Inference Benchmark
By Dana McCarty - 04 Mar, 2021 - Comments: 0

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

Making Sense Of New Edge-Inference Architectures
By Bryon Moyer - 04 Mar, 2021 - Comments: 0

New edge-inference machine-learning architectures have been arriving at an astounding rate over the last year. Making sense of them all is a challenge. To begin with, not all ML architectures are alike. One of the complicating factors in understanding the different machine-learning architectures is the nomenclature used to describe them. You’ll see terms like “sea-of-MACs,” “systolic... » 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

Timing Challenges In The Age Of AI Hardware
By Quiyang Wu - 25 Feb, 2021 - Comments: 0

In recent years, we have seen a clear market trend towards dedicated integrated circuits (ASICs) that are much more efficient in performance and energy consumption than traditional general-purpose computers for processing AI workloads. These AI accelerators harden deep learning algorithm kernels into circuits, enable higher data ingestion bandwidth with local memory, and perform massively paral... » read more

Big Challenges In Verifying Cyber-Physical Systems
By Ed Sperling - 25 Feb, 2021 - Comments: 0

Semiconductor Engineering sat down to discuss cyber-physical systems and how to verify them with Jean-Marie Brunet, senior director for the Emulation Division at Siemens EDA; Frank Schirrmeister, senior group director for solution marketing at Cadence; Maurizio Griva, R&D Manager at Reply; and Laurent Maillet-Contoz, system and architect specialist at STMicroelectronics. This discussion was... » read more

Part Average Tests For Auto ICs Not Good Enough
By Anne Meixner - 24 Feb, 2021 - Comments: 0

Part Average Testing (PAT) has long been used in automotive. For some semiconductor technologies it remains viable, while for others it is no longer good enough. Automakers are bracing for chips developed at advanced process nodes with much trepidation. Tight control of their supply chains and a reliance upon mature electronic processes so far have enabled them to increase electronic compone... » read more

What Do Feedback Loops For AI/ML Devices Really Show?
By Ed Sperling - 09 Feb, 2021 - Comments: 0

AI/ML is being designed into an increasing number of chips and systems these days, but predicting how they will behave once they're in the field is, at best, a good guess. Typically, verification, validation, and testing of systems is done before devices reach the market, with an increasing amount of in-field data analysis for systems where reliability is potentially mission- or safety-criti... » read more

Addressing Power Challenges In AI Hardware
By Solaiman Rahim - 04 Feb, 2021 - Comments: 0

Artificial intelligence (AI) accelerators are essential for tackling AI workloads like neural networks. These high-performance parallel computation machines provide the processing efficiency that such high data volumes demand. With AI playing increasingly larger roles in our lives—from consumer devices like smart speakers to industrial applications like automated factories—it’s paramount ... » read more

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