Abstract: Detection of soft errors and faults are one of the most critical factors in ensuring the reliability of algorithm implementations. Multiplication, as a fundamental and computationally ...

Discovering faster algorithms for matrix multiplication remains a key pursuit in computer science and numerical linear algebra. Since the pioneering contributions of Strassen and Winograd in the late ...

Comstock Park — Marshmallows, math and hot cocoa created the perfect equation for a little multiplication on a snowy Friday morning at Pine Island Elementary. Students in Rachel Haveman’s third-grade ...

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 ...

Hi @RobertCsordas thank you for the update regarding dtype, this is very helpful, let me check what is going on with float16 on Volta. Regarding Triton version PyTorch indeed pins the version for the ...

Computer scientists have discovered a new way to multiply large matrices faster than ever before by eliminating a previously unknown inefficiency, reports Quanta Magazine. This could eventually ...

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 ...

The authors do not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and have disclosed no relevant affiliations beyond their ...