Performance results for benchmarks from NAS NPB 3.3 is updated. These benchmarks has been parallelized using Fortran-DVMH language and were executed on graphics accelerators NVIDIA, on 6-cores processor Intel and on 60-cores Intel Xeon Phi.
Parallel computational technologies (PCT) 2017 was held on April 3rd - 7th, 2017 in Russia, Kazan:Kazan, Kazan Federal University.
Automated parallelization of a simulation method of elastic wave propagation in media with complex 3D geometry surface on high-performance heterogeneous clusters
The paper considers application of DVM and SAPFOR systems in order to automate mapping of 3D elastic waves simulation method on high-performance heterogeneous clusters. A distinctive feature of the proposed method is the use of a curved threedimensional grid, which is consistent with the geometry of free surface. Usage of curved grids considerably complicates both manual and automated parallelization. Technique to map curved grid on a structured grid has been presented to solve this problem. The sequential program based on the finite difference method on a structured grid, has been parallelized using Fortran-DVMH programming language. Application of SAPFOR analysis tools simplified this parallelization process. The paper describes features of automated parallelization. Authors estimate efficiency and acceleration of the parallel program and compare performance of the DVMH-based program with a program obtained after manual parallelization using MPI programming technology.
Presented by A.S. Kolganov.
Parallel Large-Scale Graph Processing was held on March 2nd, 2017 in Russia, Moscow, Lomonosov Moscow State University.
DVM-system was designed to create parallel programs of scientific-technical calculations in C-DVMH and Fortran-DVMH languages. These languages use the same model of parallel programming (DVMH-model) and are the extensions of standard C and Fortran languages with parallelism specifications, implemented as compiler directives. DVMH-model allows to create efficient parallel programs for heterogeneous computational clusters, which nodes use as computing devices not only universal multi-core processors but also can use attached accelerators (GPUs or Intel Xeon Phi coprocessors). This report discusses new means to work with irregular grids, which were implemented in the C-DVMH compiler recently. Using the developed extension can significantly ease irregular grid applications parallelization on cluster.
Presented by A.S. Kolganov.
DVM system was installed at Siberian Supercomputer Center on NKS-30T supercomputer of Institute of Computational Mathematics and Mathematical Geophysics of Siberian Branch of Russian Academy of Sciences (ICMMG SB RAS). Instruction how to use DVM-sysytem on NKS-30T is available here. The instructions for all computer systems where DVM system is installed are here.
Supercomputing and mathematical simulation 2016 was held on October 3rd - 7th, 2016 in Russia, Sarov, RUSSIAN FEDERAL NUCLEAR CENTER ALL-RUSSIAN RESEARCH INSTITUTE OF EXPERIMENTAL PHYSICS.
Implementation of parallel program for compositional flow simulation during oil and gas fields development using DVM-system
Compositional multiphase simulation is used for more detailed flow modeling for reservoirs with light hydrocarbons (gas, condensate), for more accurate description of mass exchange between phases in enhanced oil recovery methods such as carbon dioxide or nitrogen injection, enriched gas injection or high-pressure gas injection. The main stages of the development of the parallel version of the multiphase filtering program with use of DVM system will be considered in the presentation.
Presented by A.V. Korolev, V.A. Bakhtin.