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

TL;DR

This paper presents the vision and current implementation of HPCAdvisor, a tool designed to assist users in defining their HPC clusters in the cloud that considers the application’s input and utilizes a major cloud provider as a use case for its back-end component.

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.

Figures (10)

• Figure 1: Overview of the HPCAdvisor tool.
• Figure 2: Plot example: Execution Time vs. Number of Nodes.
• Figure 3: Plot example: Execution Time vs. Cost.
• Figure 4: Plot example: Speed up.
• Figure 5: Plot example: Efficiency.