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: Matrix-vector multiplication is practically used in all Digital Signal Processing (DSP) algorithms. Particularly, in the channel emulation field, it is required to perform this algorithm in ...

MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat instead of electricity. These tiny structures could someday enable more ...

In 2023, the website then known as Twitter partially open sourced its algorithm for the first time. In those days, Tesla billionaire Elon Musk had only recently acquired the platform, and he claimed ...

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 ...