AlphaTensor, builds upon AlphaZero, an agent that has shown superhuman performance on board games, like chess, Go and shogi, and this work shows the journey of AlphaZero from playing games to tackling ...

Abstract: Fast matrix multiplication is one of the most fundamental problems in algorithm research. The exponent of the optimal time complexity of matrix multiplication is usually denoted by $\omega$.

Semidynamics has announced a RISC-V Tensor Unit that is designed for ultra-fast AI solutions and is based on its fully customisable 64-bit cores. State-of-the-art Machine Learning models, such as ...

Machine learning research is progressing at an ever-faster pace. We are likely still decades away from reaching the singularity, but AI has already become the buzzword that every tech company is ...

Abstract: Recently, as DNN has demonstrated extraordinary performance and efficiency in areas such as image processing and target recognition, research on DNN (deep neural network) and its dedicated ...

The 'algorithm for calculating the matrix product' that AlphaTensor worked on this time is used in various fields related to daily life, such as image processing, game graphics processing, weather ...

Multiplying the content of two x-y matrices together for screen rendering and AI processing. Matrix multiplication provides a series of fast multiply and add operations in parallel, and it is built ...

I'm trying to test matrix multiplication on V100 using cutlass 3.9.2 and simulate the process using Accel-sim, but found that when the matrix size is small (e.g. m,n,k=512 and m,n,k=1024) everything ...