Population Annealing and Large Scale Simulations in Statistical Mechanics
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.
The model of distributed calculators makes it possible a parallel calculation of the correlated N-particle system with a complex multi-particle interaction (long-range ionic and short-range repulsive, two- and three-particle covalent interactions) with MPI and CUDA technologies. The computational model is based on the mathematical model of heterogeneous descriptors developed by the authors, that allows shift the focus from the describing the physical interactions in the system to the description of data flow between the descriptors. The results of computer experiments, which compare the time of the simulation on the cluster of 16 calculators and GPU NVIDIA are given. The model of distributed calculators was being tested with the software package of RIS «MD-SLAG-MELT»
One of the most important problems, by development of the automated systems of scientific researches is providing efficient performance of computers. The algorithm for tasks division among the processors of molecular-dynamic sub-systems modeling of the research-informational system Slag Melt system is described. The authors recommend the method of optimizing the algorithm as well as an estimation and calculation of the system efficiency and improving its operation.
Now we have the need for methodics of teaching the topic "parallel computing" in secondary school. The paper presents a three-year experience of the author in this field: a methodical approach, the selection of materials, the business games, experience of tasks on parallel computing at the contest "TRIZformashka", classes of tasks, examples of tasks, program executors, texts for propaedeutic textbook on informatics.
The new version of the program complex intended for numerical modeling of propagation and transformation of internal gravity waves in the ocean, with a finalized unit calculation of a ray of internal waves and with a paralleling of the program, which can significantly speed up the ongoing computation is presented. As a practical example of the proposed study addictive properties of the shelf of the Baltic Sea from the point of view of long internal waves on the basis of the ray approach is offered. The values of the coefficient of capture are calculated and the corresponding maps are constructed.
In this paper, we present an approach to scalable co-scheduling in distributed computing for complex sets of interrelated tasks(jobs). The scalability means that schedules are formed for job models with various levels of task granularity, data replication policies, and processor resource and memory can be upgraded. The necessary of guaranteed job execution at the required quality of service causes taking into account the distributed environment dynamics, namely, changes in the number of jobs for servicing, volumes of computations, possible failures of processor nodes, etc. At a consequence, in the general case, a set of versions of scheduling, or a strategy, is required instead of a single version. We propose a callable model of scheduling based on multicriteria strategies. The choice of the specific schedule depends on the load level of the resource dynamics and is formed as a resource query which is sent to a local batch-job management system.
The article is devoted to inclusion of the topic "parallel computing" in the school informatics . Some methodical materials prepared in the course of work on the "Permian version" of a propaedeutic course of computer science (the author team is M.A. Plaksin, N.I. Ivanova, O.L. Rusakova) are described.
This book constitutes the refereed proceedings of the 12th International Conference on Parallel Computational Technologies, PCT 2018, held in Rostov-on-Don, Russia, in April 2018.
The 24 revised full papers presented were carefully reviewed and selected from 167 submissions. The papers are organized in topical sections on high performance architectures, tools and technologies; parallel numerical algorithms; supercomputer simulation.
This book is collection of research papers included in the program of the International Scientific Conference "Parallel Computing Technologies 2016". The conference was held from 28 March to 1 April 2016 the Northern (Arctic) Federal University (Arkhangelsk). For more information about the conference can be found on the Internet at the following address http://agora.guru.ru/pavt.