Year: 2024
Type: conference-paper
Abstract: This study explores strategies for academic re-searchers to optimize computational resources within limited budgets, focusing on building small, efficient computing clusters. It delves into the comparative costs of purchasing versus renting servers, guided by market research and economic theories on tiered pricing. The paper offers detailed insights into the selection and assembly of hardware components such as CPUs, GPUs, and motherboards tailored to specific research needs. It introduces innovative methods to mitigate the performance issues caused by PCIe switch bandwidth limitations in order to enhance GPU task scheduling. Furthermore, a Graph Neural Network (GNN) framework is proposed to analyze and optimize parallelism in computing networks.
Authors: Ruilong WU, Yisu Wang, Dirk KUTSCHER
Language: English
Subfield: Hardware and Architecture
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Award: G537185493
OpenAlex ID: W4404239339