Improve Ocean Modelling Software NEMO 4.0 benchmarking and communication efficiency

Communications in distributed memory supercomputers are still limiting scalability of geophysical models. Consid-ering the recent trends of the semiconductor industry, we think this problem is here to stay. We present the optimisations thathave been implemented in the actual 4.0 reference version of the ocean model NEMO 4.0 to improve its scalability. Thanksto the collaboration of oceanographers and HPC experts, we identified and removed the unnecessary communications in twobottleneck routines, the computation of free surface pressure gradient and the forcing in the straights or unstructured open5boundaries. Since a wrong parallel decomposition choice could undermine computing performance, we impose its automaticdefinition in all cases, including when subdomains containing land points only are excluded from the decomposition. For asmaller audience of developers and vendors, we propose a new benchmark configuration, easy to use while offering the fullcomplexity of operational versions.

Parallel decomposition of control algorithms for computational processes based on the use of nondeterministic automaton logic

The paper deals with the issues of decomposition of control algorithms for the processes in parallel computing systems and the use of automaton models. When designing parallel processing systems, an important task is the formal presentation of process control algorithms since they allow achieving a packaged solution to the problems of specification, development, implementation, verification, and analysis of complex control systems, including the control of interacting processes and resources in parallel computing systems. It is especially necessary to use formal methods to verify complex information processing systems by model testing. One of the methods for the formal description of control algorithms is based on the use for these purposes of the nondeterministic automaton (NDA) logic, which is a method that allows one to present control algorithms for information processing in the form of systems of canonical equations describing all particular events implemented in the algorithm. The advantage of such a language is that all transitions in the control system are described not in terms of system states, but in terms of particular events, the simultaneous existence of which determines all states and transitions in the system; this allows avoiding a "combinatorial explosion" in the state space to the possibilities of means verification. Purpose of the paper: research of control algorithms for parallel computing systems using the NDA apparatus. The development and research object is parallel decomposition of control algorithms for parallel computing systems using automatic models.

Fast and Parallel Decomposition of Constraint Satisfaction Problems

Constraint Satisfaction Problems (CSP) are notoriously hard. Consequently, powerful decomposition methods have been developed to overcome this complexity. However, this poses the challenge of actually computing such a decomposition for a given CSP instance, and previous algorithms have shown their limitations in doing so. In this paper, we present a number of key algorithmic improvements and parallelisation techniques to compute so-called Generalized Hypertree Decompositions (GHDs) faster. We thus advance the ability to compute optimal (i.e., minimal-width) GHDs for a significantly wider range of CSP instances on modern machines. This lays the foundation for more systems and applications in evaluating CSPs and related problems (such as Conjunctive Query answering) based on their structural properties.