On Wednesday, Meta unveiled four new artificial intelligence chips: The MTIA 300, MTIA 400, MTIA 450, and the MTIA 500.

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 ...

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 ...

Parallel Computing starter project to build GPU & CPU kernels in CUDA & C++ and call them from Python without a single line of CMake using PyBind11 ...

Discovering faster algorithms for matrix multiplication remains a key pursuit in computer science and numerical linear algebra. Since the pioneering contributions of Strassen and Winograd in the late ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Newton iteration algorithm. Compared to other algorithms, Newton ...

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most difficult tasks in numerical ...

The Nature Index 2025 Research Leaders — previously known as Annual Tables — reveal the leading institutions and countries/territories in the natural and health sciences, according to their output in ...

If you bought an Nvidia RTX 5090, 5080, 5070 Ti, or (probably) the upcoming RTX 5070, you should check if it's missing ROPs and therefore you're missing out on performance. As many as 0.5% of all ...

Abstract: Matrix multiplication is a cornerstone operation in a wide array of scientific fields, including machine learning and computer graphics. The standard ...