On a dynamic scheduling algorithm for massively parallel computations of atomic isotopes

The goal of the work is to enhance the execution scalability of the code called AtomicClusters for evaluations of in-medium properties of nuclear clusters to extreme scales. In order to fully exploit the computing power of massively parallel supercomputing systems, the code was supplemented with parallel output and dynamic scheduling system based on task-stealing technique. The scheduling system was implemented for state-of-the-art distributed-memory high-performance computers (HPC) using the advanced features of Message Passing Interface (MPI) as an independent adjustable module. The parallel output was integrated into the code using MPI IO. A number of strong scaling tests was performed for the resulting parallel software. An almost linear scalability was reached on up to 4000 cores. The code scales up to at least 38400 processes, but with lower speedup. The obtained results are discussed in the fifth section of the paper.