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 ...

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 ...

This project is intended for research purposes only. Use it at your own risk and discretion. Triton is a language and compiler for writing highly efficient ML primitives, one of the most common ...

Using a grid, the system designs a set of rectangular silicon structures filled with tiny pores. The system continually adjusts each pixel in the grid until it arrives at the desired mathematical ...

Heat diffuses through the silicon in a way that performs the matrix multiplication, with the geometry of the structure encoding the coefficients. "These structures are far too complicated for us to ...