A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Implementations of matrix multiplication via diffusion and reactions, thus eliminating ...

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 ...

/// @brief Module for handling the matrix-vector multiplication as a part of solving the 1d PDE for heat diffusion. /// Options are: /// 1. 'manual' : using explicit triple loop for matrix-vector ...

Since homomorphic encryption enables SIMD operations by packing multiple values into a vector of operations and enabling pairwise addition or multiplication operations, one (old) conventional method ...

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 ...

Abstract: One popular application for big data is matrix multiplication, which has been solved using many approaches. Recently, researchers have applied MapReduce as a new approach to solve this ...

PyTorch introduced TK-GEMM, an optimized Triton FP8 GEMM kernel, to address the challenge of accelerating FP8 inference for large language models (LLMs) like Llama3 using Triton Kernels. Standard ...

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 ...