Abstract: Sparse-sparse matrix multiplication (SpGEMM) is a well-studied problem on CPUs, GPUs, accelerators (e.g. FPGAs), and distributed systems. The main computational bottleneck in SpGEMM is the ...
Abstract: Sparse General Matrix-Matrix Multiplication (SpGEMM) is a core operation in high-performance computing applications such as algebraic multigrid solvers, machine learning, and graph ...
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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 ...