Modeling exascale data generation and storage for the large hadron collider computing network

The Large Hadron Collider (LHC) is the world's largest and highest energy particle accelerator. With the particle collisions produced at the LHC and measured with the Compact Muon Solenoid (CMS) detector, the CMS experimental group performs precision measurements and general searches for new physics. Year-round CMS operations produce 100 Petabytes of physics data per year, which is stored within a globally distributed grid network of 70 scientific institutions. By 2027, upgrades to the LHC and CMS detector will allow unprecedented probes of microscopic physics, but in doing so generate 2,000 Petabytes (2 Exabytes) of physics data per year. To address the computational requirements of CMS, the cost of CPU resources, disk and tape storage, and tape drives were modeled. These resources were then used in a model of the major CMS computing processes and required infrastructure.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Computation for Design and Optimization Program

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2020

Author dc:creator

• Massaro, Evan K.

Advisor dc:contributor.advisor

• Markus Klute and John Williams.

• Computation for Design and Optimization Program.

Statement dc:rights

• MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/126990

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/126990