Supercomputing. RuSCDays 2018. Communications in Computer and Information Science, vol 965. Springer, Cham
This book constitutes the refereed proceedings of the 4th Russian Supercomputing Days, RuSCDays 2018, held in Moscow, Russia, in September 2018.
The 59 revised full papers and one revised short paper presented were carefully reviewed and selected from 136 submissions. The papers are organized in topical sections on parallel algorithms; supercomputer simulation; high performance architectures, tools and technologies.
Modern Elbrus-4S and Elbrus-8S processors show floating point performance comparable to the popular Intel processors in the field of high-performance computing. Tasks oriented to take advantage of the VLIW architecture show even greater efficiency on Elbrus processors. In this paper the efficiency of the most popular materials science codes in the field of classical molecular dynamics and quantum-mechanical calculations is considered. A comparative analysis of the performance of these codes on Elbrus processor and other modern processors is carried out.
Population annealing is a novel Monte Carlo algorithm designed for simulations of systems of statistical mechanics with rugged free-energy landscapes. We discuss a realization of the algorithm for the use on a hybrid computing architecture combining CPUs and GPGPUs. The particular advantage of this approach is that it is fully scalable up to many thousands of threads. We report on applications of the developed realization to several interesting problems, in particular the Ising and Potts models, and review applications of population annealing to further systems.
High-performance computing plays an increasingly important role in modern science and technology. However, the lack of convenient interfaces and automation tools greatly complicates the widespread use of HPC resources among scientists. The paper presents an approach to solving these problems relying on Everest, a web-based distributed computing platform. The platform enables convenient access to HPC resources by means of domain-specific computational web services, development and execution of many-task applications, and pooling of multiple resources for running distributed computations. The paper describes the improvements that have been made to the platform based on the experience of integration with resources of supercomputing centers. The use of HPC resources via Everest is demonstrated on the example of loosely coupled many-task application for solving global optimization problems.