A major design challenge facing numerous silicon design teams in 2023 is building the right amount of machine learning (ML) performance capability into today’s silicon tape out in anticipation of what the state of the art (SOTA) ML inference models will look like in 2026 and beyond when that silicon will be used in devices in volume production. Given the continuing rapid rate of change in mac... » read more
This new technical paper titled "End-to-end deep learning framework for printed circuit board manufacturing defect classification" is from researchers at École de technologie supérieure (ÉTS) in Montreal, Quebec.
Abstract
"We report a complete deep-learning framework using a single-step object detection model in order to quickly and accurately detect and classify the types of manufacturi... » read more
As more designers employ machine learning (ML) in their systems, they’re moving from simply getting the application to work to optimizing the power and performance of their implementations. Some techniques are available today. Others will take time to percolate through the design flow and tools before they become readily available to mainstream designers.
Any new technology follows a basic... » read more
Geoff Tate, CEO of Flex Logix, talks about the importance of hardware-software co-design for inference accelerators, how that affects performance and power, and what new approaches chipmakers are taking to bring AI chips to market.
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Geoff Tate, CEO of Flex Logix, talks with Semiconductor Engineering about how to measure efficiency in inferencing chips, how to achieve the most throughput for the lowest cost, and what the benchmarks really show.
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Geoff Tate, CEO of Flex Logix, talks about benchmarking in edge devices, particularly for convolutional neural networks.
https://youtu.be/-beVEpKAM4M » read more
eBook: Nearly everything you need to know about memory, including detailed explanations of the different types of memory; how and where these are used today; what's changing, which memories are successful and which ones might be in the future; and the limitations of each memory type.
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