HEPCloud, a New Paradigm for HEP Facilities: CMS Amazon Web Services Investigation

TL;DR

This paper explores the use of cloud computing, specifically AWS, for high energy physics data processing, demonstrating its feasibility, challenges, and economic benefits alongside traditional dedicated resources.

Contribution

It presents the first large-scale implementation of CMS workflows on AWS, highlighting technical, operational, and economic insights for cloud-based HEP computing.

Findings

Successful execution of CMS workflows on AWS cloud

Identified technical challenges and solutions in cloud computing for HEP

Demonstrated cost and operational efficiencies of cloud resources

Abstract

Historically, high energy physics computing has been performed on large purpose-built computing systems. These began as single-site compute facilities, but have evolved into the distributed computing grids used today. Recently, there has been an exponential increase in the capacity and capability of commercial clouds. Cloud resources are highly virtualized and intended to be able to be flexibly deployed for a variety of computing tasks. There is a growing nterest among the cloud providers to demonstrate the capability to perform large-scale scientific computing. In this paper, we discuss results from the CMS experiment using the Fermilab HEPCloud facility, which utilized both local Fermilab resources and virtual machines in the Amazon Web Services Elastic Compute Cloud. We discuss the planning, technical challenges, and lessons learned involved in performing physics workflows on a large-scale set of virtualized resources. In addition, we will discuss the economics and operational efficiencies when executing workflows both in the cloud and on dedicated resources.