Originally posted by LordHawkwind
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In chips past RDNA 3, this is probably going to be game changing. 3D stacked chiplet Radeons... with a deep learning FPGA Xilinx chip.
But there is probably more to the shift to newer FPGA iron at Xilinx than just some of the Super 8 doing big rollouts. First, the Vitis environment for programming FPGAs from Xilinx has made it easier to deploy them as industry-specific and application-specific offload engines, and with the slowdown in Moore’s Law, there is greater need to do something. Both the GPU and the FPGA have emerged as a new kind of general-purpose offload engine, and the FPGA is getting its share here.
AMD has been working on different ways to speed up AI calculations for years. First the company announced and released the Radeon Impact series of AI accelerators, which were just big headless Radeon graphics processors with custom drivers. The company doubled down on that with the release of the MI60, its first 7-nm GPU ahead of the Radeon RX 5000 series launch, in 2018. A shift to focusing on AI via FPGAs after the Xilinx acquisition makes sense, and we're excited to see what the company comes up with.
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