For those interested in using linear algebra in a symbolic setting, or for working with matrices over the integers or rational numbers (not float point numbers) you'll be interested in using the SymPy ...

Visualizing linear transformations. Matrix-vector multiplication: a linear combination of the matrix columns. Some special transformations: rotation, shear, scaling. Matrix-matrix multiplication: a ...

Enhancing Deep Learning with nvmath-python's Matrix Multiplication and Epilog Fusion. Tony Kim Nov 18, 2024 23:24. Discover how nvmath-python leverages NVIDIA CUDA-X math libraries for ...

CLA is a simple toy library for basic vector/matrix operations in C. This project main goal is to learn the foundations of CUDA, and Python bindings, using ctypes as a wrapper, through simple Linear ...

Despite C/C++ and Python both being very popular programming languages, each tool possesses unique advantages and disadvantages. Notably, computers can run C/C++ code very quickly, but C/C++ code has ...

If you are using SymPy in conjuction with other Python libraries you will want to use prefixes to indicate what library you intend to be used. For example, either use import sympy as sy, then each ...

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.

The library shows substantial speed improvements in matrix multiplication tasks, particularly when handling large float16 matrices, as commonly required in deep learning applications. Moreover, nvmath ...