2019
DOI: 10.1007/s10586-019-02960-y
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Approaches of enhancing interoperations among high performance computing and big data analytics via augmentation

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Cited by 10 publications
(2 citation statements)
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“…erefore, it is a typical combinatorial optimization problem, which aims to study discrete space through certain mathematical methods. e solution of combinatorial optimization problem is mainly divided into two parts: mathematical model establishment and optimal solution search process [16]. e intelligent optimization algorithm is the sum of the theoretical methods to find the optimal solution of the problem under the condition of feasible solutions and constraints through a certain optimization process based on a certain search mechanism.…”
Section: Multicycle Order Allocation Distribution Designmentioning
confidence: 99%
“…erefore, it is a typical combinatorial optimization problem, which aims to study discrete space through certain mathematical methods. e solution of combinatorial optimization problem is mainly divided into two parts: mathematical model establishment and optimal solution search process [16]. e intelligent optimization algorithm is the sum of the theoretical methods to find the optimal solution of the problem under the condition of feasible solutions and constraints through a certain optimization process based on a certain search mechanism.…”
Section: Multicycle Order Allocation Distribution Designmentioning
confidence: 99%
“…While these modifications enhance QP scalability, the high cost and potential impact on NIC reliability make them impractical for deployment in hyper scale AI infrastructure. Additionally, congestion control algorithms like DCQCN and TIMELY, used in these studies, cannot completely prevent collisions of multiple large flows at specific nodes (usually refers to servers or switches) in extremely large-scale AI training networks [6,9,11,18], leading to congestion in network traffic at those points.…”
Section: Introductionmentioning
confidence: 99%