NoT: a high-level no-threading parallel programming method for heterogeneous systems

2019 ◽  
Vol 75 (7) ◽  
pp. 3810-3841 ◽  
Author(s):  
Shusen Wu ◽  
Xiaoshe Dong ◽  
Xingjun Zhang ◽  
Zhengdong Zhu
2008 ◽  
Vol 4 (2) ◽  
pp. 131-146 ◽  
Author(s):  
R. Aversa ◽  
B. Di Martino ◽  
N. Mazzocca ◽  
S. Venticinque

Parallel programming effort can be reduced by using high level constructs such as algorithmic skeletons. Within the MAGDA toolset, supporting programming and execution of mobile agent based distributed applications, we provide a skeleton-based parallel programming environment, based on specialization of Algorithmic Skeleton Java interfaces and classes. Their implementation include mobile agent features for execution on heterogeneous systems, such as clusters of WSs and PCs, and support reliability and dynamic workload balancing. The user can thus develop a parallel, mobile agent based application by simply specialising a given set of classes and methods and using a set of added functionalities.


Author(s):  
Mario Rossainz López ◽  
Ivo H. Pineda-Torres ◽  
Ivan Olmos Pineda ◽  
José Arturo Olvera López

Within an environment of parallel objects, an approach of structured parallel programming and the paradigm of the orientation to objects show a programming method based on high level parallel compositions or HLPCs to solve two problems of combinatorial optimization: grouping fragments of DNA sequences and the parallel exhaustive search (PES) of RNA strings that help the sequence and the assembly of DNAs. The pipeline and farm models are shown as HLPCs under the object orientation paradigm and with them it is proposed the creation of a new HLPCs that combines and uses the previous ones to solve the cited problems. Each HLPC proposal contains a set of predefined synchronization constraints between processes, as well as the use of synchronous, asynchronous and asynchronous future modes of communication. This article shows the algorithms that solve the problems, their design and implementation as HLPCs and the performance metrics in their parallel execution using multicores and video accelerator card.


Author(s):  
Loris Belcastro ◽  
Fabrizio Marozzo ◽  
Domenico Talia ◽  
Paolo Trunfio

2021 ◽  
Vol 24 (1) ◽  
pp. 157-183
Author(s):  
Никита Андреевич Катаев

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.


2018 ◽  
Vol 84 ◽  
pp. 22-31 ◽  
Author(s):  
Adrián Castelló ◽  
Rafael Mayo ◽  
Kevin Sala ◽  
Vicenç Beltran ◽  
Pavan Balaji ◽  
...  

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