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The article discusses Matrix Core Programming on AMD's CDNA3 and CDNA4 architectures, focusing on the implementation of low-precision data types like FP16, FP8, and FP4 in HIP kernels. It highlights how Matrix Cores enhance performance in AI and HPC workloads through matrix multiplication. The piece also explains the advantages of using lower-precision data types and presents various MFMA instructions alongside performance calculations, and compiler intrinsics for programming these cores.