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Google AI Introduces STATIC: A Sparse Matrix Framework Delivering 948x Faster Constrained Decoding for LLM Based Generative Retrieval

In industrial recommendation systems, the shift toward Generative Retrieval (GR) is replacing traditional embedding-based nearest neighbor search with Large Language Models (LLMs). These models ...
IEEE

Accelerating Sparse Matrix-Matrix Multiplication by Adaptive Batching Strategy on MGPUSim

Abstract: Sparse Matrix-Matrix Multiplication (SpMM) is a widely used algorithm in Machine Learning, particularly in the increasingly popular Graph Neural Networks (GNNs). SpMM is an essential ...
Hosted on MSN

Allies and algorithms: The matrix and partnerships shaping AI’s future

CNBC's Squawk Box Asia Martin Soong and Chery Kang talk about AMD's chip supply deal with OpenAI, plus the web of alliances, cross shareholdings and the money loop that could shape the AI space. Trump ...
GitHub

[REQ] Allocation-free path for masked sparse matrix operations

Currently many operations in wp.sparse modify the end matrix topology, using CUB-backed reductions that require temporary storage allocations under the hood. As a result, then cannot be captured in ...
C&EN

QCMaquis 4.0: Multipurpose Electronic, Vibrational, and Vibronic Structure and Dynamics Calculations with the Density Matrix Renormalization Group

You are free to share (copy and redistribute) this article in any medium or format within the parameters below: Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must ...
Visual Studio Magazine

Matrix Inverse Using Cayley-Hamilton with C#

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...