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Jon Peddie Research’s FPGAs in AI report is a supply-side report; it covers the companies building field-programmable chips for AI inference at the edge and in the cloud, and IoTs.
The FPGAs in AI report defines FPGA processors and how they are used.
The report also contains information about the companies in this segment and their technology and products, as well as the approaches each company is taking.
FPGA processors are not a replacement for GPUs or NPUs — they are typically used as test chips and low-volume devices where the time and cost of designing and building an ASIC don’t make sense. The JPR report covers the architecture, competitive landscape, and commercial trajectory of FPGAs for AI chips from Altera/Intel, AMD/Xilinx, Flex Logix, Lattice Semiconductor, and QuickLogic.
Description
FPGAs (field-programmable gate arrays) occupy a distinctive position in the AI processor landscape. Unlike fixed-function GPUs, NPUs, or ASICs, an FPGA contains arrays of configurable logic blocks that designers can program and reprogram to implement any digital circuit — including custom neural processing hardware. This programmability gives FPGAs a unique capability: A developer can map an AI inference workload directly to hardware and reshape that hardware as models evolve, without the cost or lead time of a new silicon tape-out.
The report covers the architecture, competitive landscape, and commercial trajectory of FPGAs being used for AI.
The report includes competitive profiles, a supplier table, market size and unit shipment forecasts through 2031, ASP analysis by segment, and more
The FPGAs in AI Report is a valuable resource for understanding the FPGA market, providing insight into the capabilities of these processors today and coming in the near future.
FPGAs in AI Report Table of Contents
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