28 September 2015 to 2 October 2015
Budva, Becici, Hotel Splendid, Conference Hall
Europe/Podgorica timezone

Integration Of PanDA Workload Management System With Supercomputers

2 Oct 2015, 10:00
Budva, Becici, Hotel Splendid, Conference Hall

Budva, Becici, Hotel Splendid, Conference Hall


Dr Alexei Klimentov (Brookhaven National Lab)


Abstract. The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe, and were recently credited for the discovery of a Higgs boson. ATLAS, one of the largest collaborations ever assembled in the sciences, is at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, the ATLAS experiment is relying on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Management System for managing the workflow for all data processing on over 140 data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. While PanDA currently uses more than 100,000 cores with a peak performance of 0.3 petaFLOPS, next LHC data taking runs will require more resources than Grid computing can possibly provide. To alleviate these challenges, LHC experiments are engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. We will describe a project aimed at integration of PanDA WMS with supercomputers in United States, Europe and Russia (in particular with Titan supercomputer at Oak Ridge Leadership Computing Facility (OLCF), Supercomputer at the National Research Center “Kurchatov Institute”, IT4 in Ostrava and others). Current approach utilizes modified PanDA pilot framework for job submission to the supercomputers batch queues and local data management, with light-weight MPI wrappers to run single threaded workloads in parallel on Titan's multi-core worker nodes. This implementation was tested with a variety of Monte-Carlo workloads on several supercomputing platforms. We will present our current accomplishments with running PanDA WMS at supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facilities infrastructure for High Energy and Nuclear Physics as well as other data-intensive science applications, such as bioinformatics and astro-particle physics.

Primary author

Dr Alexei Klimentov (Brookhaven National Lab)


Mr Alexander Novikov (NRC KI) Dr Alexei Poyda (NRC KI) Mr Danila Oleynik (JINR LIT) Mr Eygene Ryabinkin (NRC KI) Dr Jack Wells (ORNL) Prof. Kaushik De (UTA) Prof. Ken Read (ORNL) Dr Paul Nilsson (BNL) Dr Ruslan Mashinistov (NRC KI) Dr Sergey Panitkin (BNL) Prof. Shantenu Jha (Rutgers University) Dr Tadashi Maeno (BNL) Dr torre wenaus (BNL)

Presentation Materials