Sparse matrix-matrix multiplication (SpMM) is a crucial kernel in various applications, including sparse deep neural networks [1]–[6], graph analytics [7], triangle counting [8], and linear algebra ...
Abstract: Accurate programming of non-volatile memory (NVM) devices in analog in-memory computing (AIMC) cores is critical to achieve high matrix-vector multiplication (MVM) accuracy during deep ...
Quantum-inspired adaptive tiling for high-performance matrix multiplication. Uses WKB tunneling physics with the golden ratio to derive optimal tile sizes from real-time CPU state. 15%+ gains on ...
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