Abstract: This paper formulates the shared-link cache-aided matrix multiplication retrieval problem. Matrix multiplication is an essential building block for distributed computing applications.

Abstract: While the Karatsuba algorithm reduces the complexity of large integer multiplication, the extra additions required minimize its benefits for smaller integers of more commonly-used bitwidths.

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.

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Implementing 3D shape transformations using matrix multiplication and a basic line scan-conversion algorithm. In order to run the main program, you must have a version of Python that is 3.6+ and have ...

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NumPy is known for being fast, but could it go even faster? Here’s how to use Cython to accelerate array iterations in NumPy. NumPy gives Python users a wickedly fast library for working with data in ...

Optical computing uses photons instead of electrons to perform computations, which can significantly increase the speed and energy efficiency of computations by overcoming the inherent limitations of ...