Towards a distributed heterogeneous task scheduler for the ATLAS offline software framework

With the increased data volumes expected to be delivered by the HL-LHC, it becomes critical for the ATLAS experiment to maximize the utilization of available computing resources ranging from conventional GRID clusters to supercomputers and cloud computing platforms. To be able to run its data processing applications on these resources, the ATLAS software framework must be capable of efficiently executing data processing tasks in heterogeneous distributed computing environments. Today with the use of the Gaudi Avalanche Scheduler, whose implementation is based on Intel TBB, we can efficiently schedule Athena algorithms to multiple threads within a single compute node. Our goal is to develop a new framework scheduler capable of supporting distributed heterogeneous environments, based on technologies like HPX or Ray. After the initial evaluation phase of these technologies, we began the development of a prototype distributed task scheduler for the Athena framework. This contribution will describe this prototype scheduler and the preliminary results of performance studies within ATLAS data processing applications.