Article information

2015 , Volume 20, ¹ 4, p.17-28

Borisenko A.B., Karpushkin S.V.

Using of OpenMP for optimal choice of process equipment for multiproduct batch plants

In this work, we parallelize the Branch-and-Bound (B&B) algorithm and illustrate it with a practical application - the optimal selection of equipment for multi-product batch plants. We develop and evaluate an implementation of the parallel B&B method on a multicore system with shared memory using C++ programming language and OpenMP version 3.0 (Open Multi-Processing) for the task-based approach. To limit the degree of parallelism to a certain level of the tree we introduce a granularity parameter G: subtrees below the granularity level are not split into tasks but rather processed sequentially. We conducted our runtime experiments on a computer consisting of 4 CPUs with the total of 32 cores. We analyzed the impact of the degree of parallelism controlled by the granularity parameter on the runtime and show the analysis for speedup and efficiency of the processors’ usage. Selecting a suitable granularity value is crucial for optimal performance, but with a large number of tasks we may not have enough memory. It happends when G > 10 in our case. Implementation of our algorithm has near-linear speedup and provide high parallel scalability. Efficiency of processors’ usage is shown to be 0.9 - 0.95.

[full text]
Keywords: Discrete optimization, parallel branch-and-bound method, OpenMP, multiproduct batch plants, choice of process equipment

Borisenko Andrey Borisovich
PhD. , Associate Professor
Office: Tambov State Technical University
Address: 392000, Russia, Tambov, Sovetskaya Str. 106
Phone Office: (4752) 630706

Karpushkin Sergey Viktorovich
Dr. , Professor
Position: Professor
Office: Tambov State Technical University
Address: 392000, Russia, Tambov, Sovetskaya Str. 106
Phone Office: (4752) 630706

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Bibliography link:
Borisenko A.B., Karpushkin S.V. Using of OpenMP for optimal choice of process equipment for multiproduct batch plants // Computational technologies. 2015. V. 20. ¹ 4. P. 17-28
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