Abstract: Matrix-matrix multiplication (MM) of large matrices plays a crucial role in various applications, including machine learning. MM requires significant computational resources, but accessing ...
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 ...
NVIDIA releases detailed cuTile Python tutorial for Blackwell GPUs, demonstrating matrix multiplication achieving over 90% of cuBLAS performance with simplified code. NVIDIA has published a ...
This is a simple f2py-wrapper for the logarithmic FFT code FFTLog as presented in Appendix B of [Hami00] and published at casa.colorado.edu/~ajsh/FFTLog. A pure ...
I'm a Fitness & Nutrition writer for CNET who enjoys reviewing the latest fitness gadgets, testing out activewear and sneakers, as well as debunking wellness/fitness myths. In my free time I enjoy ...
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 ...
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