Kamal Mann is a Software Architect with over 22 years of experience in Industry 4.0 systems. He currently advises on edge ...

Abstract: Efficient representation of sparse matrices is critical for reducing memory usage and improving performance in hardware-accelerated computing systems. This letter presents memory-efficient ...

The minimal reproducible code is described below. Consider a standard autocast training framework, where a weight matrix is a learnable parameter stored in float type; and input is a sparse_csr ...

ABSTRACT: Node renumbering is an important step in the solution of sparse systems of equations. It aims to reduce the bandwidth and profile of the matrix. This allows for the speeding up of the ...

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.