Federal health officials now recommend that children be routinely inoculated against 11 diseases, not 17, citing standards in other wealthy nations. By Apoorva Mandavilli Federal health officials on ...

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.

Researchers claim to have developed a new way to run AI language models more efficiently by eliminating matrix multiplication from the process. This fundamentally redesigns neural network operations ...

Most neural network topologies heavily rely on matrix multiplication (MatMul), primarily because it is essential to many basic processes. Vector-matrix multiplication (VMM) is commonly used by dense ...

Abstract: Sparse matrix multiplication is an important component of linear algebra computations. Implementing sparse matrix multiplication on an associative processor (AP) enables high level of ...

Computer scientists are a demanding bunch. For them, it’s not enough to get the right answer to a problem — the goal, almost always, is to get the answer as efficiently as possible. Take the act of ...

If the first or last factor is a number, this will be fused with the matrix multiplication, using 5-arg mul!. See also muladd, dot. │ Julia 1.7 │ │ These optimisations require at least Julia 1.7.