In the present run of the LHC, CMS data reconstruction and simulation algorithms benefit greatly from being executed as multiple threads running on several processor cores. The complexity of the Run-2 events requires parallelization of the code in order to reduce the memory-per-core footprint constraining serial-execution programs, thus optimizing the exploitation of present multi-core processor architectures. The allocation of computing resources for multi-core tasks however becomes a complex problem in itself. The CMS workload submission infrastructure employs multi-slot partitionable pilots, built on HTCondor and GlideinWMS native features, to enable the scheduling of single and multi-core jobs simultaneously. This provides a solution for the scheduling problem in a uniform way across grid sites running a diversity of gateways to compute resources and batch system technologies. This contribution will present this strategy and the tools on which it has been implemented. The experience of managing multi-core resources at the Tier-0 and Tier-1 sites during 2015 will be described, along with the current phase of deployment to Tier-2 sites during 2016. The process of performance monitoring and optimization in order to achieve efficient and flexible use of the resources will also be described.
|Primary Keyword (Mandatory)||Distributed workload management|
|Secondary Keyword (Optional)||Computing models|