tag: TPUs

Data Formats For Inference On The Edge
By Brian Bailey - 14 Dec, 2023 - Comments: 0

AI/ML training traditionally has been performed using floating point data formats, primarily because that is what was available. But this usually isn't a viable option for inference on the edge, where more compact data formats are needed to reduce area and power. Compact data formats use less space, which is important in edge devices, but the bigger concern is the power needed to move around... » read more

Complex Tradeoffs In Inferencing Chips
By John Koon - 17 Oct, 2022 - Comments: 0

Designing AI/ML inferencing chips is emerging as a huge challenge due to the variety of applications and the highly specific power and performance needs for each of them. Put simply, one size does not fit all, and not all applications can afford a custom design. For example, in retail store tracking, it's acceptable to have a 5% or 10% margin of error for customers passing by a certain aisle... » read more

New Uses For AI In Chips
By John Koon and Ed Sperling - 11 Aug, 2022 - Comments: 1

Artificial intelligence is being deployed across a number of new applications, from improving performance and reducing power in a wide range of end devices to spotting irregularities in data movement for security reasons. While most people are familiar with using machine learning and deep learning to distinguish between cats and dogs, emerging applications show how this capability can be use... » read more

Toward Democratized IC Design And Customized Computing
By Jason Cong - 28 Jun, 2022 - Comments: 0

Integrated circuit (IC) design is often considered a “black art,” restricted to only those with advanced degrees or years of training in electrical engineering. Given that the semiconductor industry is struggling to expand its workforce, IC design must be rendered more accessible. The benefit of customized computing General-purpose computers are widely used, but their performance improv... » read more

Repositioning For A Changing IC Market
By Ed Sperling - 26 May, 2022 - Comments: 0

Sailesh Chittipeddi, executive vice president at Renesas, sat down with Semiconductor Engineering to talk about how changes in end markets are shifting demand for technology. What follows are excerpts of that conversation. SE: Renesas has acquired a number of companies over the past several years. What's the goal? Chittipeddi: The goal very simply is to create an industry leading solutio... » read more

Gaps In The AI Debug Process
By Brian Bailey - 23 Nov, 2021 - Comments: 0

When an AI algorithm is deployed in the field and gives an unexpected result, it's often not clear whether that result is correct. So what happened? Was it wrong? And if so, what caused the error? These are often not simple questions to answer. Moreover, as with all verification problems, the only way to get to the root cause is to break the problem down into manageable pieces. The semico... » read more

Hidden Costs In Faster, Low-Power AI Systems
By Ed Sperling - 20 Jan, 2021 - Comments: 1

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

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