Research and Application of Parallel Computing under Linux

2013 ◽  
Vol 756-759 ◽  
pp. 2825-2828
Author(s):  
Xue Chun Wang ◽  
Quan Lu Zheng
Keyword(s):  
Parallel Computing ◽  
Parallel Processing ◽  
High Performance Computing ◽  
Parallel Programming ◽  
High Performance ◽  
Performance Testing ◽  
Divide And Conquer ◽  
Parallel Computer ◽  
Super Computing ◽  
Performance Computing

Parallel computing is in parallel computer system for parallel processing of data and information, often also known as the high performance computing or super computing. The content of parallel computing were introduced, the realization of parallel computing and MPI parallel programming under Linux environment were described. The parallel algorithm based on divide and conquer method to solve rectangle placemen problem was designed and implemented with two processors. Finally, Through the performance testing and comparison, we verified the efficiency of parallel computing.

Parallel computing

2018 ◽  
Author(s):  
Joseph F. Boudreau ◽  
Eric S. Swanson
Keyword(s):  
Monte Carlo ◽  
Parallel Computing ◽  
High Performance Computing ◽  
Parallel Programming ◽  
High Performance ◽  
Parallel Application ◽  
Client Server ◽  
Parallel Code ◽  
Performance Computing

This chapter describes various approaches to concurrency, or “parallel programming”. An overview of high performance computing is followed with a review of Flynn’s taxonomy of parallel computing. Three methods for implementing parallel code using the frameworks provided by MPI, openMP, and C++ threads are presented. The use of the C++ constructs mutex and future to resolve issues of synchronization are discussed. All methods are illustrated with an embarrassingly parallel application to a Monte Carlo integral and common pitfalls are presented. The chapter closes with a discussion and example of the utility of forking processes and the use of C++ sockets and their application in a client/server environment.

scholarly journals METHODS AND ALGORITHMS FOR PARALLEL CALCULATIONS USING VIRTUALIZATION TECHNOLOGIES IN MATERIALS SCIENCE PROBLEMS

2021 ◽  
Author(s):  
Vadim Kondrashev ◽  
Sergey Denisov
Keyword(s):  
Parallel Computing ◽  
High Performance Computing ◽  
Material Science ◽  
High Performance ◽  
Applied Research ◽  
Materials Science ◽  
Parallel Calculations ◽  
Computing Technologies ◽  
Integrated Software ◽  
Performance Computing

The paper discusses methods and algorithms for the provision of high-performance computing resources in multicomputer systems in a shared mode for fundamental and applied research in the field of materials science. Approaches are proposed for the application of applied integrated software environments (frameworks) designed to solve material science problems using virtualization and parallel computing technologies.

Comparing High-Performance Computing Techniques for Modeling Structural Impact on Battery Cells

2014 ◽  
Author(s):  
Mehdi Gilaki ◽  
Ilya Avdeev
Keyword(s):  
Finite Element ◽  
Parallel Processing ◽  
High Performance Computing ◽  
High Performance ◽  
Strain Curve ◽  
Thin Layers ◽  
Massively Parallel ◽  
Structural Impact ◽  
Performance Computing ◽  
Battery Cells

In this study, we have investigated feasibility of using commercial explicit finite element code LS-DYNA on massively parallel super-computing cluster for accurate modeling of structural impact on battery cells. Physical and numerical lateral impact tests have been conducted on cylindrical cells using a flat rigid drop cart in a custom-built drop test apparatus. The main component of cylindrical cell, jellyroll, is a layered spiral structure which consists of thin layers of electrodes and separator. Two numerical approaches were considered: (1) homogenized model of the cell and (2) heterogeneous (full) 3-D cell model. In the first approach, the jellyroll was considered as a homogeneous material with an effective stress-strain curve obtained through experiments. In the second model, individual layers of anode, cathode and separator were accounted for in the model, leading to extremely complex and computationally expensive finite element model. To overcome limitations of desktop computers, high-performance computing (HPC) techniques on a HPC cluster were needed in order to get the results of transient simulations in a reasonable solution time. We have compared two HPC methods used for this model is shared memory parallel processing (SMP) and massively parallel processing (MPP). Both the homogeneous and the heterogeneous models were considered for parallel simulations utilizing different number of computational nodes and cores and the performance of these models was compared. This work brings us one step closer to accurate modeling of structural impact on the entire battery pack that consists of thousands of cells.

Large Scale Mosaic Using Parallel Computing for Remote Sensed Images

2014 ◽  
Vol 556-562 ◽  
pp. 4746-4749
Author(s):  
Bin Chu ◽  
Da Lin Jiang ◽  
Bo Cheng
Keyword(s):  
Parallel Computing ◽  
High Performance Computing ◽  
High Performance ◽  
Large Scale ◽  
Computing System ◽  
Physical Relationship ◽  
High Performance Computing System ◽  
Performance Computing

This paper concerns about Large-scale mosaic for remote sensed images. Base on High Performance Computing system, we offer a method to decompose the problem and integrate them with logical and physical relationship. The mosaic of Large-scale remote sensed images has been improved both at performance and effectiveness.

scholarly journals IDEA OF ARCHITECTURE OF A MULTIPROCESSOR COMPUTER M-10 AND THEIR IMPLEMENTATION IN MODERN COMPUTING PLATFORMS (IN SMALL FORMS)

2019 ◽  
pp. 28-31
Author(s):  
E. V. Glivenko ◽  
S. А. Sorokin ◽  
G. N. Petrovа
Keyword(s):  
Parallel Processing ◽  
High Performance Computing ◽  
High Performance ◽  
Multiprocessor Computer ◽  
M 10 ◽  
Operator Type ◽  
Computing Platforms ◽  
Main Ideas ◽  
New Generation ◽  
Performance Computing

The article is devoted to the design of high‑performance computing devices for parallel processing of information. The problem of  increasing the productivity of computing facilities by one or several orders of magnitude is considered on the example of the high‑ performance electronic computer M‑10, which was created in the 1970s at the NIIVK. If in a conventional computer, the method  of processing numbers is given by commands, then in M‑10, the methods for processing a function were specified by operators  taken from functional analysis. At the same time, the possibility of parallel processing of an entire information line appeared. Such  systems began to be called «functional operator type machines». The main ideas presented in the article may be of interest to  developers of specialized machines of the new generation, as well as engineers involved in the creation of high‑performance  computing devices using technologies of computing platforms.

scholarly journals Computational experiment in era of HPC

2019 ◽  
Vol 27 (3) ◽  
pp. 263-267
Author(s):  
Alexander S. Ayriyan
Keyword(s):  
Parallel Computing ◽  
Life Cycle ◽  
High Performance Computing ◽  
High Performance ◽  
Computational Experiment ◽  
Computing Systems ◽  
The Impact ◽  
Performance Computing

In this note we discuss the impact of development of architecture and technology of parallel computing on the typical life-cycle of the computational experiment. In particular, it is argued that development and installation of high-performance computing systems is indeed important itself regardless of specific scientific tasks, since the presence of cutting-age HPC systems within an academic infrastructure gives wide possibilities and stimulates new researches.

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