Learn how to use Python as a vector calculator for electric fields. This video shows how to represent charges and position vectors, compute field direction and magnitude, and solve problems faster ...

Abstract: Emerging applications, e.g., machine learning, large language models (LLMs), and graphic processing, are rapidly developing and are both compute-intensive and memory-intensive. Computing in ...

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 ...

Multiplication in Python may seem simple at first—just use the * operator—but it actually covers far more than just numbers. You can use * to multiply integers and floats, repeat strings and lists, or ...

Element-wise multiplication in Python is a fundamental operation, especially when working with numerical data using libraries like NumPy. Understanding how to perform this efficiently is crucial for ...

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.

Artificial intelligence (AI) processing rests on the use of vectorised data. In other words, AI turns real-world information into data that can be used to gain insight, searched for and manipulated.

Abstract: Sparse matrix multiplication is widely used in various practical applications. Different accelerators have been proposed to speed up sparse matrix-dense vector multiplication (SpMV), sparse ...