Bridging Machine Learning’s Divide


There is a growing divide between those researching [getkc id="305" comment="machine learning"] (ML) in the cloud and those trying to perform inferencing using limited resources and power budgets. Researchers are using the most cost-effective hardware available to them, which happens to be GPUs filled with floating point arithmetic units. But this is an untenable solution for embedded infere... » read more

Move Data Or Process In Place?


Should data move to available processors or should processors be placed close to memory? That is a question the academic community has been looking at for decades. Moving data is one of the most expensive and power-consuming tasks, and is often the limiter to system performance. Within a chip, Moore's Law has enabled designers to physically move memory closer to processing, and that has rema... » read more

Targeting And Tailoring eFPGAs


Robert Blake, president and CEO of Achronix, sat down with Semiconductor Engineering to discuss what's changing in the embedded FPGA world, why new levels of customization are so important, and difficulty levels for implementing embedded programmability. What follows are excerpts of that discussion. SE: There are numerous ways you can go about creating a chip these days, but many of the prot... » read more

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