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The 2M Multiplication Algorithm for Complex Matrices
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arXiv:2609.05419v2 Announce Type: replace Abstract: Complex matrix multiplication is typically computed using 4 real matrix multiplications (GEMMs) of the same size. The well-known 3M multiplication algorithm reduces this cost to 3 real GEMMs, together with quadratic time pre- and post-processing steps. In this paper, we reduce 3M to 2M for matrices with integer real and imaginary parts, performing complex GEMM with only 2 real GEMMs of the same size, along with quadratic time pre- and post-processing. For floating-point matrices, 2M multiplication combines naturally with the Ozaki-II scheme, yielding a practical, high-performance algorithm for computing a complex floating-point GEMM in roughly twice the time of a real GEMM of the same size. As corollaries, we derive new algorithms for symmetric rank-$k$ updates (SYRK/HERK) that internally use full rectangular GEMMs.
Source:https://arxiv.org/abs/2609.05419PreviouseAVID: Asynchronous Verifiable Information Dispersal with Post-Dissemination PruningNextDIALER: A Case for Improving Rare-Class Accuracy in Retraining-Free Edge Video Analytics
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