HPCAdvisor: A Tool for Assisting Users in Selecting HPC Resources in the Cloud

TL;DR

HPCAdvisor is a tool that helps users select appropriate cloud-based HPC resources by considering application input and cloud options, simplifying the decision process for optimal performance and cost-efficiency.

Contribution

The paper introduces HPCAdvisor, a novel tool that assists users in defining HPC clusters in the cloud based on application input and cloud provider data.

Findings

HPCAdvisor effectively guides resource selection for HPC workloads.

The tool considers application-specific input for tailored resource recommendations.

Initial implementation demonstrates practical utility in cloud HPC environments.

Abstract

Cloud platforms are increasingly being used to run HPC workloads. Major cloud providers offer a wide variety of virtual machine (VM) types, enabling users to find the optimal balance between performance and cost. However, this extensive selection of VM types can also present challenges, as users must decide not only which VM types to use but also how many nodes are required for a given workload. Although benchmarking data is available for well-known applications from major cloud providers, the choice of resources is also influenced by the specifics of the user's application input. This paper presents the vision and current implementation of HPCAdvisor, a tool designed to assist users in defining their HPC clusters in the cloud. It considers the application's input and utilizes a major cloud provider as a use case for its back-end component.