An Impact of Cross Over Operator on the Performance of Genetic Algorithm Under Operating System Process Scheduling Problem

Author(s):  
Rajiv Kumar ◽  
Sanjeev Gill ◽  
Ashwani Kaushik
Author(s):  
Jitendra Kumar Rai ◽  
Atul Negi ◽  
Rajeev Wankar ◽  
K. D. Nayak

Sharing resources such as caches and memory buses between the cores of multi-core processors may cause performance bottlenecks for running programs. In this paper, the authors describe a meta-scheduler, which adapts the process scheduling decisions for reducing the contention for shared L2 caches on multi-core processors. The meta-scheduler takes into account the multi-core topology as well as the L2 cache related characteristics of the processes. Using the model generated by the process of machine learning, it predicts the L2 cache behavior, i.e., solo-run-L2-cache-stress, of the programs. It runs in user mode and guides the underlying operating system process scheduler in intelligent scheduling of processes to reduce the contention of shared L2 caches. In these experiments, the authors observed up to 12 percent speedup in individual as well as overall performance, while using meta-scheduler as compared to default process scheduler (Completely Fair Scheduler) of Linux kernel.


2020 ◽  
Vol 53 (7-8) ◽  
pp. 1529-1539
Author(s):  
Yaqin Zhou ◽  
Junliang Wang ◽  
Peng Zhang ◽  
Pan Wang ◽  
Yingtao Lu ◽  
...  

As the most important core process in the dyeing and finishing workshop of knitting companies, the dyeing process has the characteristics of multi-variety, small-batch, parallel machine processing of multiple types, and high cost in equipment cleaning, which render the dyeing scheduling problem a bottleneck in the production management of a dyeing and finishing workshop. In this paper, the dyeing process scheduling problem in dyeing and finishing workshops is described and abstracted, and an optimized mathematical model of dyeing scheduling is constructed with the goal of minimizing the delay cost and switching cost. Constraints such as multiple types of equipment, equipment capacity, weights of orders and equipment cleaning time are considered. For the sub-problem of equipment scheduling in the dyeing scheduling problem, a heuristic rule that considers equipment utilization and order delay is proposed. For the sub-problem of order sorting of the equipment in the dyeing scheduling problem, a hybrid genetic algorithm with a variable neighbourhood search strategy has been designed to optimize sorting. The algorithm proposed in this paper has been demonstrated via case simulation to be effective in solving the scheduling problem in dyeing and finishing workshops.


Author(s):  
Jitendra Kumar Rai ◽  
Atul Negi ◽  
Rajeev Wankar ◽  
K. D. Nayak

Sharing resources such as caches and memory buses between the cores of multi-core processors may cause performance bottlenecks for running programs. In this paper, the authors describe a meta-scheduler, which adapts the process scheduling decisions for reducing the contention for shared L2 caches on multi-core processors. The meta-scheduler takes into account the multi-core topology as well as the L2 cache related characteristics of the processes. Using the model generated by the process of machine learning, it predicts the L2 cache behavior, i.e., solo-run-L2-cache-stress, of the programs. It runs in user mode and guides the underlying operating system process scheduler in intelligent scheduling of processes to reduce the contention of shared L2 caches. In these experiments, the authors observed up to 12 percent speedup in individual as well as overall performance, while using meta-scheduler as compared to default process scheduler (Completely Fair Scheduler) of Linux kernel.


2012 ◽  
pp. 522-534
Author(s):  
Jitendra Kumar Rai ◽  
Atul Negi ◽  
Rajeev Wankar ◽  
K. D. Nayak

Sharing resources such as caches and memory buses between the cores of multi-core processors may cause performance bottlenecks for running programs. In this paper, the authors describe a meta-scheduler, which adapts the process scheduling decisions for reducing the contention for shared L2 caches on multi-core processors. The meta-scheduler takes into account the multi-core topology as well as the L2 cache related characteristics of the processes. Using the model generated by the process of machine learning, it predicts the L2 cache behavior, i.e., solo-run-L2-cache-stress, of the programs. It runs in user mode and guides the underlying operating system process scheduler in intelligent scheduling of processes to reduce the contention of shared L2 caches. In these experiments, the authors observed up to 12 percent speedup in individual as well as overall performance, while using meta-scheduler as compared to default process scheduler (Completely Fair Scheduler) of Linux kernel.


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