Abstract

The PanDA (Production and Distributed Analysis) workload management system was developed to meet the scale and complexity of distributed computing for the ATLAS experiment. PanDA managed resources are distributed worldwide, on hundreds of computing sites, with thousands of physicists accessing hundreds of Petabytes of data and the rate of data processing already exceeds Exabyte per year. While PanDA currently uses more than 200,000 cores at well over 100 Grid sites, future LHC data taking runs will require more resources than Grid computing can possibly provide. Additional computing and storage resources are required. Therefore ATLAS is engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. In this paper we will describe a project aimed at integration of ATLAS Production System with Titan supercomputer at Oak Ridge Leadership Computing Facility (OLCF). Current approach utilizes modified PanDA Pilot framework for job submission to Titan’s batch queues and local data management, with lightweight MPI wrappers to run single node workloads in parallel on Titan’s multi-core worker nodes. It provides for running of standard ATLAS production jobs on unused resources (backfill) on Titan. The system already allowed ATLAS to collect on Titan millions of core-hours per month, execute hundreds of thousands jobs, while simultaneously improving Titans utilization efficiency. We will discuss the details of the implementation, current experience with running the system, as well as future plans aimed at improvements in scalability and efficiency.Notice: This manuscript has been authored, by employees of Brookhaven Science Associates, LLC under Contract No. DE-AC02-98CH10886 with the U.S. Department of Energy. The publisher by accepting the manuscript for publication acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes.

Highlights

  • The ATLAS experiment [1] is one of the four major experiments at the Large Hadron Collider (LHC)

  • In this paper we will describe a project aimed at integration of the ATLAS production system with the Titan supercomputer at the Oak Ridge Leadership Computing Facility (OLCF)

  • More details about the ATLAS production system can be found in the Ref [6]

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Summary

Introduction

The ATLAS experiment [1] is one of the four major experiments at the Large Hadron Collider (LHC). It is designed to test predictions of Standard Model and explore fundamental building blocks of matter and their interactions as well as novel physics at the highest energy available in the laboratory. In order to achieve its scientific goals ATLAS employs massive computing infrastructure. It currently uses more than 250,000 CPU cores deployed in a global Grid [2, 3],. In this paper we will describe a project aimed at integration of the ATLAS production system with the Titan supercomputer at the Oak Ridge Leadership Computing Facility (OLCF)

PanDA workload management system
ATLAS production system
Titan at OLCF
Integration with Titan
Running ATLAS production on Titan
Findings
Conclusion
Full Text
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