Sparse matrix-matrix multiplication (SpMM) is a crucial kernel in various applications, including sparse deep neural networks [1]–[6], graph analytics [7], triangle counting [8], and linear algebra ...
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 ...
If folks have libraries who are using SciPy sparse matrices, and you'd like help converting them to run/work with sparse array, this sounds like a nice opportunity to work that out. I wrote a ...
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 ...
The test suite in conda-forge/arrow-cpp-feedstock#1664 has a single test failure ===== FAILURES ===== _____ test_sparse_coo_tensor_scipy_roundtrip[f2-arrow_type8 ...
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.
A new technical paper titled “Signal processing architecture for a trustworthy 77GHz MIMO Radar” was published by researchers at Fraunhofer FHR, Ruhr University Bochum, and Wavesense Dresden GmbH.
Abstract: Based on the simulation of the combination of Python and C language, this paper simulates the dynamic scheduling of redundant nodes in the sparse multipath channel of the communication ...
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