The Google Tensor G4 on the Pixel 9 phones performs poorly on the Geekbench CPU test, despite packing the latest ARM cores. The older ARM Mali-G715 GPU on the Tensor G4 is also pretty weak, ...

Hi, thanks for your great work on Transformer Engine! I am working on a project that requires high-performance batched matrix multiplication (i.e., 3D tensor multiplication) where all inputs are ...

Abstract: We investigate the performance of algorithms for sparse tensor-sparse tensor multiplication (SpGETT). This operation, also called sparse tensor contraction, is a higher order analogue of the ...

Last year, I wrote about the massive energy costs of AI and General Purpose Transformers like ChatGPT. The AI capabilities are amazing, but the energy and environmental cost is concerning. To ...

Warp 1.5.0 launches tile-based programming in Python, leveraging cuBLASDx and cuFFTDx for efficient GPU operations, significantly improving performance in scientific computing and simulation. The ...

Parallel computing continues to advance, addressing the demands of high-performance tasks such as deep learning, scientific simulations, and data-intensive computations. A fundamental operation within ...

New Linear-complexity Multiplication (L-Mul) algorithm claims it can reduce energy costs by 95% for element-wise tensor multiplications and 80% for dot products in large language models. It maintains ...

This time, groundbreaking news came from China in the world of science and technology. China has developed the world’s first carbon nanotube-based tensor processor chip (TPU). The team led by Peng ...