## News

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.

##### Presentations

###### Automated parallelization of a simulation method of elastic wave propagation in media with complex 3D geometry surface on high-performance heterogeneous clusters

###### 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.

##### Presentations

###### The extension of DVM-system to solve the problems with intensive irregular memory access

###### The extension of DVM-system to solve the problems with intensive irregular memory access

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**.National Supercomputing Forum (NSCF-2016) was held on November 29th - December 2nd, 2016 in Russia, Pereslavl, the Program Systems Institute of RAS.

##### Presentations

###### New possibilities of automation system of parallel program development (DVM-system)

###### New possibilities of automation system of parallel program development (DVM-system)

The following recently implemented capabilities of the DVM-system are discussed in the presentation:

- new version of C-DVMH language and compiler;
- extension of C-DVM and Fortran-DVMH possibilities to solve problems with irregular grids;
- implementation of parallel I/O tools;
- new features for functional debugging and analysis of parallel programs performance.

Examples of usage of these features on test and real applications will be demonstrated.

Presented by V.A. Bakhtin.

###### Mapping of graph problems on GPU architecture - theory and practice

###### Mapping of graph problems on GPU architecture - theory and practice

Last time graphics accelerators (GPUs) GPU are increasingly being used in non-graphical computations. They’re needed because of their relatively high performance and lower cost. As you know, the problems on structured grids where the parallelism is easily determined are solved well on GPUs. But there are problems that require more computing power and use non-structured grids. The examples of such tasks are: Single Shortest Source Path problem (SSSP) – the problem to find the shortest paths from a given vertex to all the others in a weighted graph, MST (minimum spanning tree) – finding the minimum spanning forest in a graph, BFS (breadth first search) – breadth-first search in the graph, Community detection – finding closely related communities in a graph, and others. These tasks are very often used in various fields of research: a recognition of various objects, computer vision, analysis and building of networks (for example, telephone, electrical, computer, road, etc.), chemistry and biology, and in many other areas.

Presented by A.S. Kolganov.