This paper is the first part of a series of two, where the goal of this first part is to give a tutorial style introduction to modern PC architectures and GPU ...
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Other Title. A Computational Model and Algorithms to Utilize GPUs for Discrete Problems ; Author. 小池, 敦 ; Author. コイケ, アツシ ; Author. Atsushi, KOIKE.
Part II gives a broad survey of the literature on parallel computing in discrete optimization targeted at modern PCs, with special focus on routing problems.
Jul 17, 2019 · The first algorithm coming to mind that can benefit from GPUs is the Interior-Point Method (IPM), at its heart is the resolution of a linear system.
In this chapter we present intuitive mappings of standard computational concepts onto the special-purpose features of GPUs.
Apr 8, 2024 · I've implemented a genetic algorithm using the CUDA.jl package and have endeavored to utilize my NVIDIA GeForce 840M to solve these problems in parallel.
an approximated inference-based algorithm that exploits parallel computation using. GPUs to solve WCSPs and DCOPs. Our proposal aims at employing GPU hardware.
Sep 22, 2022 · This article compares the differences between a CPU and a GPU, as well as the applications for each with machine learning, neural networks, and deep learning.
Jan 23, 2012 · Problems which have a high arithmetic intensity and regular memory access patterns are typically easy(ier) to implement on GPUs, and perform well on them.
Missing: Discrete | Show results with:Discrete
Our model, called AGPU, abstracts the essence of current GPU architectures such as global and shared memory, memory coalescing and bank conflicts. We can ...