In this paper, we propose an over-the-air (OTA)-based approach for distributed matrix-vector multiplications in the context of distributed machine learning (DML). Thanks to OTA computation, the column ...

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

New Unitil solar array in Kingston expected to generate 9.7 million kWh in first year of operation Sorry, this video is not available, please check back later.

Sparse Matrix: A full-featured library in Python for working with Sparse Matrix.

According to Haerang Choi and colleagues at SK hynix, in a presentation at IEDM, matrix-vector multiplication accounts for 90% of the response phase workload. [3] Because it requires less than one ...

Add a description, image, and links to the matrix-vector-multiplication topic page so that developers can more easily learn about it ...

We introduce the CROSS compiler (1) to adopt Barrett reduction to provide modular reduction support using multiplier and adder, (2) Basis Aligned Transformation (BAT) to convert high-precision ...

Discover how nvmath-python leverages NVIDIA CUDA-X math libraries for high-performance matrix operations, optimizing deep learning tasks with epilog fusion, as detailed by Szymon Karpiński.

Abstract: We propose a high-density vertical AND-type (V-AND) flash thin-film transistor (TFT) array enabling accurate vector-matrix multiplication (VMM) operations. Compared to the planar AND-type (P ...