Abstract: We propose an efficient quantum subroutine for matrix multiplication that computes a state vector encoding the entries of the product of two matrices in superposition. The subroutine ...
Two former Google DeepMind researchers who worked on the company’s Nobel Prize-winning AlphaFold protein structure prediction ...
A growing number of AI processors are being designed around specific workloads rather than standardized benchmarks, ...
This repository contains the CUDA kernels for general matrix-matrix multiplication (GEMM) and the corresponding performance analysis. The correctness of the CUDA kernels is guaranteed for any matrix ...
This is the official implementation of our ICLR 2025 paper "UniCO: On Unified Combinatorial Optimization via Problem Reduction to Matrix-Encoded General TSP". Fig 1. The 3-step workflow of the UniCO ...
Abstract: In this paper, an adaptive neurodynamic algorithm based on multi-agent system is proposed to solve the multi-constraint matrix-valued optimization problem. The optimization problem with ...
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