Conversations about artificial intelligence still start and finish with NVIDIA on most trading mornings. Its GPUs, which are ...

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 ...

Large language models such as ChaptGPT have proven to be able to produce remarkably intelligent results, but the energy and monetary costs associated with running these massive algorithms is sky high.

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Matrix multiplications (MatMul) are the ...

Matrix multiplication (MatMul) is a fundamental operation in most neural networks, primarily because GPUs are highly optimized for these computations. Despite its critical role in deep learning, ...

I have the sense that some perspective is missing here. People should remember that every Boomer didn't spring wholly evil from the mind of a mid-1940's supervillain. The father figures of the Boomers ...

Abstract: In the light bulb problem, one is given as input vectors $x_{1}, \ldots, x_{n}, y_{1}, \ldots, y_{n} \in\{-1,1\}^{d}$ which are all uniformly random. They ...

Abstract: Distributed computing has made it possible to satisfy the demands for large-scale matrix multiplication. A distributed computing system suffers from both straggler problem and information ...