NVIDIA integrates Universal Sparse Tensor into nvmath-python v0.9.0, boosting sparse deep learning and scientific computing with zero-cost PyTorch interoperability. Why it matters: Sparse data is a ...

Abstract: Sparse-Sparse matrix multiplication (SpMSpM) is a critical computation in various fields such as computational science and graph analysis. It poses computational challenges for ...

Ever wonder why ChatGPT slows down during long conversations? The culprit is a fundamental mathematical challenge: Processing long sequences of text requires massive computational resources, even with ...

Abstract: Sparse arrays offer economic advantages by reducing the number of antennas. However, directly utilizing the covariance matrix of sparse array signals for wideband beamforming may lead to the ...

Is this real life? Is this just fantasy? A growing number of scientists are suggesting that the idea that we are all living in a simulation may not be completely far-fetched. Simulation theory is the ...

This project focuses on lossless compression techniques optimizing space, time, and energy for multiplications between binary (or ternary) matrix formats and real-valued vectors.

A new technical paper titled “Signal processing architecture for a trustworthy 77GHz MIMO Radar” was published by researchers at Fraunhofer FHR, Ruhr University Bochum, and Wavesense Dresden GmbH.