Hybrid cluster of multicore CPUs and GPUs for accelerating hyperspectral image hierarchical segmentation

Hossam, Mahmoud; Ebied, Hala M.; Abdelaziz, M.

doi:10.1109/icces.2013.6707216

Cited by 4 publications

(1 citation statement)

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“…In [21], Hawick et al described the use of threading approaches and multi-core CPUs to control independent GPU devices to speed up scientific simulations. Hossam et al [22] introduced a parallel implementation of hybrid CPU/GPU in which CPU and GPU work cooperatively and seamlessly, combining benefits of both platforms. All these works have verified that a scheme exploiting a multi-core CPU and GPUs corporately can increase the hardware occupation and achieve a speedup.…”

Section: Literature Reviewmentioning

confidence: 99%

Solving the dynamic energy aware job shop scheduling problem with the heterogeneous parallel genetic algorithm

Luo

Baz

Xue

et al. 2020

Future Generation Computer Systems

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Integrating energy savings into production efficiency is considered as one essential factor in modern industrial practice. A lot of research dealing with energy efficiency problems in the manufacturing process focuses solely on building a mathematical model within a static scenario. However, in the physical world shop scheduling problems are dynamic where unexpected events may lead to changes in the original schedule after the start time. This paper makes an investigation into minimizing the total tardiness, the total energy cost and the disruption to the original schedule in the job shop with new urgent arrival jobs. Because of the NP hardness of this problem, a dual heterogeneous island parallel genetic algorithm with the event driven strategy is developed. To reach a quick response in the dynamic scenario, the method we propose is made with a two-level parallelization where the lower level is appropriate for concurrent execution within GPUs or a multi-core CPU while codes from the two sides can be executed simultaneously at the upper level. In the end, numerical tests are implemented and display that the proposed approach can solve the problem efficiently. Meanwhile, the average results have been improved with a significant execution time decrease.

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Section: Literature Reviewmentioning

confidence: 99%