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## Concurrently Employing Resources of Several Supercomputers With Parascip Solver By Everest Platform

ParaSCIP is rather advanced open-source solver for discrete and global optimization problems. This solver is distinguished by that it can run on distributed memory systems and use up to 80,000 cores, solving open problems from the MIPLIB test libraries. Earlier, using this solver, we confirmed the conjecture on optimal packing of nine congruent circles on a square flat torus. The goal of the study was to increase computing performance by utilizing resources of multiple clusters to solve hard optimization problem. To do this, we use the previously developed DDBNB application, which allows to speed up the solution of optimization problems by using coarse-grained parallelization based on a static decomposition of feasible domain made before solving starts. DDBNB is an application for the Everest distributed computing platform which is responsible for running jobs on heterogeneous computing resources (servers, cloud instances, clusters, etc.). As a result, DDBNB, Everest, and ParaSCIP had to be modified to make it possible to exchange incumbents (feasible solutions found by the solver) between several ParaSCIP instances running on different supercomputers. The resulting system was benchmarked using three different instances of Traveling Salesman Problem. The supercomputers HPC5 of the NRC “Kurchatov Institute” and cHARISMa of the HSE University were used as computing resources. As a result, for two problem instances, there is an effect, and the speedup is especially noticeable for a more complex problem. However, for a simpler problem, the exchange of incumbents does not seem to affect the amount of speedup. For the third instance, there is no particular effect, at least no slowdown is observed.