Generation of shortest path search dataflow networks of actors for parallel multi-core implementation

Abstract

Objectives. The problem of parallelizing computations on multicore systems is considered. On the Floyd – Warshall blocked algorithm of shortest paths search in dense graphs of large size, two types of parallelism are compared: fork-join and network dataflow. Using the CAL programming language, a method of developing actors and an algorithm of generating parallel dataflow networks are proposed. The objective is to improve performance of parallel implementations of algorithms which have the property of partial order of computations on multicore processors.Methods. Methods of graph theory, algorithm theory, parallelization theory and formal language theory are used.Results. Claims about the possibility of reordering calculations in the blocked Floyd – Warshall algorithm are proved, which make it possible to achieve a greater load of cores during algorithm execution. Based on the claims, a method of constructing actors in the CAL language is developed and an algorithm for automatic generation of dataflow CAL networks for various configurations of block matrices describing the lengths of the shortest paths is proposed. It is proved that the networks have the properties of rate consistency, boundedness, and liveness. In actors running in parallel, the order of execution of actions with asynchronous behavior can change dynamically, resulting in efficient use of caches and increased core load. To implement the new features of actors, networks and the method of their generation, a tunable multi-threaded CAL engine has been developed that implements a static dataflow model of computation with bounded sizes of buffers. From the experimental results obtained on four types of multi-core processors it follows that there is an optimal size of the network matrix of actors for which the performance is maximum, and the size depends on the number of cores and the size of graph.Conclusion. It has been shown that dataflow networks of actors are an effective means to parallelize computationally intensive algorithms that describe a partial order of computations over decomposed data. The results obtained on the blocked algorithm of shortest paths search prove that the parallelism of dataflow networks gives higher performance of software implementations on multicore processors in comparison with the fork-join parallelism of OpenMP.