MapReduce Parallel Programming Model: A State-of-the-Art Survey

2015 ◽  
Vol 44 (4) ◽  
pp. 832-866 ◽  
Author(s):  
Ren Li ◽  
Haibo Hu ◽  
Heng Li ◽  
Yunsong Wu ◽  
Jianxi Yang
Keyword(s):  
Parallel Programming ◽  
Programming Model ◽  
State Of The Art ◽  
Parallel Programming Model

scholarly journals Portable multi-node LQCD Monte Carlo simulations using OpenACC

2018 ◽  
Vol 29 (01) ◽  
pp. 1850010 ◽  
Author(s):  
Claudio Bonati ◽  
Enrico Calore ◽  
Massimo D’Elia ◽  
Michele Mesiti ◽  
Francesco Negro ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Parallel Programming ◽  
Programming Model ◽  
State Of The Art ◽  
Computer Architectures ◽  
Monte Carlo Code ◽  
Processor Architectures ◽  
Parallel Programming Model ◽  
High Level

This paper describes a state-of-the-art parallel Lattice QCD Monte Carlo code for staggered fermions, purposely designed to be portable across different computer architectures, including GPUs and commodity CPUs. Portability is achieved using the OpenACC parallel programming model, used to develop a code that can be compiled for several processor architectures. The paper focuses on parallelization on multiple computing nodes using OpenACC to manage parallelism within the node, and OpenMPI to manage parallelism among the nodes. We first discuss the available strategies to be adopted to maximize performances, we then describe selected relevant details of the code, and finally measure the level of performance and scaling-performance that we are able to achieve. The work focuses mainly on GPUs, which offer a significantly high level of performances for this application, but also compares with results measured on other processors.

scholarly journals Parallel programming model for the Epiphany many-core coprocessor using threaded MPI

2016 ◽  
Vol 43 ◽  
pp. 95-103 ◽  
Author(s):  
James A. Ross ◽  
David A. Richie ◽  
Song J. Park ◽  
Dale R. Shires
Keyword(s):  
Parallel Programming ◽  
Programming Model ◽  
Parallel Programming Model ◽  
Many Core

scholarly journals Interaction with the User in the SAPFOR System

2021 ◽  
Vol 24 (1) ◽  
pp. 157-183
Author(s):  
Никита Андреевич Катаев
Keyword(s):  
Parallel Programming ◽  
Program Transformation ◽  
Heterogeneous Computing ◽  
Programming Model ◽  
Parallel Programs ◽  
Parallel Program ◽  
Program Parallelization ◽  
Parallel Programming Model ◽  
The One ◽  
High Level

Automation of parallel programming is important at any stage of parallel program development. These stages include profiling of the original program, program transformation, which allows us to achieve higher performance after program parallelization, and, finally, construction and optimization of the parallel program. It is also important to choose a suitable parallel programming model to express parallelism available in a program. On the one hand, the parallel programming model should be capable to map the parallel program to a variety of existing hardware resources. On the other hand, it should simplify the development of the assistant tools and it should allow the user to explore the parallel program the assistant tools generate in a semi-automatic way. The SAPFOR (System FOR Automated Parallelization) system combines various approaches to automation of parallel programming. Moreover, it allows the user to guide the parallelization if necessary. SAPFOR produces parallel programs according to the high-level DVMH parallel programming model which simplify the development of efficient parallel programs for heterogeneous computing clusters. This paper focuses on the approach to semi-automatic parallel programming, which SAPFOR implements. We discuss the architecture of the system and present the interactive subsystem which is useful to guide the SAPFOR through program parallelization. We used the interactive subsystem to parallelize programs from the NAS Parallel Benchmarks in a semi-automatic way. Finally, we compare the performance of manually written parallel programs with programs the SAPFOR system builds.

Actors as a parallel programming model

2005 ◽  
pp. 184-195 ◽  
Author(s):  
Françoise Baude ◽  
Guy Vidal-Naquet
Keyword(s):  
Parallel Programming ◽  
Programming Model ◽  
Parallel Programming Model
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