scholarly journals Scheduling computations with provably low synchronization overheads

2021 ◽  
Author(s):  
Guilherme Rito ◽  
Hervé Paulino
Keyword(s):  
Great Improvement ◽  
Execution Time ◽  
Path Length ◽  
State Of The Art ◽  
Critical Path ◽  
Scheduling Algorithm ◽  
Algorithm Design ◽  
Work Stealing ◽  
Maximum Cost

Abstract We present a Work Stealing scheduling algorithm that provably avoids most synchronization overheads by keeping processors’ deques entirely private by default and only exposing work when requested by thieves. This is the first paper that obtains bounds on the synchronization overheads that are (essentially) independent of the total amount of work, thus corresponding to a great improvement, in both algorithm design and theory, over state-of-the-art Work Stealing algorithms. Consider any computation with work T1 and critical-path length T1 executed by P processors using our scheduler. Our analysis shows that the expected execution time is O T1 P + T1 , and the expected synchronization overheads incurred during the execution are at most O ((CCAS + CMF ence) P T1), where CCAS and CMF ence respectively denote the maximum cost of executing a Compare-And-Swap instruction and a Memory Fence instruction.

scholarly journals AN EXACT SOLUTION FOR THE RESOURCE-CONSTRAINED CONSTRUCTION SCHEDULING PROBLEM

2016 ◽  
Vol 8 (2) ◽  
pp. 71-78
Author(s):  
Bartłomiej Sroka ◽  
Elżbieta Radziszewska-Zielina
Keyword(s):  
Execution Time ◽  
Critical Path ◽  
Scheduling Problem ◽  
Resource Constrained ◽  
Building Projects ◽  
Construction Scheduling ◽  
Program Sample ◽  
Resource Constrained Scheduling Problem ◽  
The Cost ◽  
Exponential Complexity

Reduced time and, by the same token, the cost of the project is a crucial factor in contemporary construction. This article presents a method for the exact optimisation of a resource-constrained scheduling problem. Based on the Critical Path Method, graph theory and linear programming, an algorithm was developed and the FROPT program was written in Matlab to minimise the execution time of the task. By using the newly-created program, sample networks were calculated and the results were compared with results obtained by using the MS Project scheduling program (using approximation algorithm). The execution time obtained by using FROPT were on average 10% shorter than those obtained using MS Project. In selected cases the improvement in execution time reached 25%. A deterministic approach to the problem may shorten planned project times and bring financial benefits. Due to the exponential complexity of the algorithm, it is most useful in solving small or highly coherent networks. The algorithm and program may result in benefits not offered by commercial software for planners of building projects.

High Performance CGM-based Parallel Algorithms for the Optimal Binary Search Tree Problem

2016 ◽  
Vol 8 (4) ◽  
pp. 55-77 ◽  
Author(s):  
Vianney Kengne Tchendji ◽  
Jean Frederic Myoupo ◽  
Gilles Dequen
Keyword(s):  
Parallel Algorithms ◽  
Execution Time ◽  
High Performance ◽  
Scheduling Algorithm ◽  
Search Tree ◽  
Binary Search ◽  
Coarse Grained ◽  
Binary Search Tree ◽  
Parameter Dependent ◽  
The Impact

In this paper, the authors highlight the existence of close relations between the execution time, efficiency and number of communication rounds in a family of CGM-based parallel algorithms for the optimal binary search tree problem (OBST). In this case, these three parameters cannot be simultaneously improved. The family of CGM (Coarse Grained Multicomputer) algorithms they derive is based on Knuth's sequential solution running in time and space, where n is the size of the problem. These CGM algorithms use p processors, each with local memory. In general, the authors show that each algorithms runs in with communications rounds. is the granularity of their model, and is a parameter that depends on and . The special case of yields a load-balanced CGM-based parallel algorithm with communication rounds and execution steps. Alternately, if , they obtain another algorithm with better execution time, say , the absence of any load-balancing and communication rounds, i.e., not better than the first algorithm. The authors show that the granularity has a crucial role in the different techniques they use to partition the problem to solve and study the impact of each scheduling algorithm. To the best of their knowledge, this is the first unified method to derive a set of parameter-dependent CGM-based parallel algorithms for the OBST problem.

An Algorithm for Task Scheduling in Heterogeneous Distributed Systems Using Task Duplication

2011 ◽  
Vol 3 (1) ◽  
pp. 89-97 ◽  
Author(s):  
Amrit Agrawal ◽  
Pranay Chaudhuri
Keyword(s):  
Task Scheduling ◽  
Execution Time ◽  
High Speed ◽  
Critical Path ◽  
Task Assignment ◽  
Directed Acyclic Graphs ◽  
Parallel Tasks ◽  
Schedule Length ◽  
Task Duplication ◽  
Heterogeneous Distributed Systems

Task scheduling in heterogeneous parallel and distributed computing environment is a challenging problem. Applications identified by parallel tasks can be represented by directed-acyclic graphs (DAGs). Scheduling refers to the assignment of these parallel tasks on a set of bounded heterogeneous processors connected by high speed networks. Since task assignment is an NP-complete problem, instead of finding an exact solution, scheduling algorithms are developed based on heuristics, with the primary goal of minimizing the overall execution time of the application or schedule length. In this paper, the overall execution time (schedule length) of the tasks is reduced using task duplication on top of the Critical-Path-On-a-Processor (CPOP) algorithm.

scholarly journals Dynamic Job Scheduling Strategy Using Jobs Characteristics in Cloud Computing

Symmetry ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 1638 ◽  
Author(s):  
Mohammed A. Alsaih ◽  
Rohaya Latip ◽  
Azizol Abdullah ◽  
Shamala K. Subramaniam ◽  
Kamal Ali Alezabi
Keyword(s):  
Execution Time ◽  
Job Scheduling ◽  
Scheduling Algorithm ◽  
Job Characteristics ◽  
Available Bandwidth ◽  
Scheduling Strategy ◽  
Cloud Users ◽  
Performance Variations ◽  
Available Resources

A crucial performance concern in distributed decentralized environments, like clouds, is how to guarantee that jobs complete their execution within the estimated completion times using the available resources’ bandwidth fairly and efficiently while considering the resource performance variations. Formerly, several models including reservation, migration, and replication heuristics have been implemented to solve this concern under a variety of scheduling techniques; however, they have some undetermined obstacles. This paper proposes a dynamic job scheduling model (DTSCA) that uses job characteristics to map them to resources with minimum execution time taking into account utilizing the available resources bandwidth fairly to satisfy the cloud users quality of service (QoS) requirements and utilize the providers’ resources efficiently. The scheduling algorithm makes use of job characteristics (length, expected execution time, expected bandwidth) with regards to available symmetrical and non-symmetrical resources characteristics (CPU, memory, and available bandwidth). This scheduling strategy is based on generating an expectation value for each job that is proportional to how these job’s characteristics are related to all other jobs in total. That should make their virtual machine choice closer to their expectation, thus fairer. It also builds a feedback method which deals with reallocation of failed jobs that do not meet the mapping criteria.

A Novel Approach in Scheduling Of the Real- Time Tasks In Heterogeneous Multicore Processor with Fuzzy Logic Technique For Micro-grid Power Management

2018 ◽  
Vol 9 (1) ◽  
pp. 80
Author(s):  
Lavanya Dhanesh ◽  
P. Murugesan
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Power Management ◽  
Execution Time ◽  
High Performance ◽  
Scheduling Algorithm ◽  
Multicore Processor ◽  
Heterogeneous Multicore ◽  
Micro Grid ◽  
Low Performance

Scheduling of tasks based on real time requirement is a major issue in the heterogeneous multicore systemsfor micro-grid power management . Heterogeneous multicore processor schedules the serial tasks in the high performance core and parallel tasks are executed on the low performance cores. The aim of this paper is to implement a scheduling algorithm based on fuzzy logic for heterogeneous multicore processor for effective micro-grid application. Real – time tasks generally have different execution time and dead line. The main idea is to use two fuzzy logic based scheduling algorithm, first is to assign priority based on execution time and deadline of the task. Second , the task which has assigned higher priority get allotted for execution in high performance core and remaining tasks which are assigned low priority get allotted in low performance cores. The main objective of this scheduling algorithm is to increase the throughput and to improve CPU utilization there by reducing the overall power consumption of the micro-grid power management systems. Test cases with different task execution time and deadline were generated to evaluate the algorithms using  MATLAB software.

Benefiting feature selection by the discovery of false irrelevant attributes

2015 ◽  
Vol 13 (04) ◽  
pp. 1550023 ◽  
Author(s):  
Lidia S. Chao ◽  
Derek F. Wong ◽  
Philip C. L. Chen ◽  
Wing W. Y. Ng ◽  
Daniel S. Yeung
Keyword(s):  
Feature Selection ◽  
Execution Time ◽  
Classification Accuracy ◽  
State Of The Art ◽  
Classification Task ◽  
Selection Methods ◽  
Empirical Results ◽  
Selection Accuracy ◽  
Irrelevant Attributes ◽  
Selection Methodology

The ordinary feature selection methods select only the explicit relevant attributes by filtering the irrelevant ones. They trade the selection accuracy for the execution time and complexity. In which, the hidden supportive information possessed by the irrelevant attributes may be lost, so that they may miss some good combinations. We believe that attributes are useless regarding the classification task by themselves, sometimes may provide potentially useful supportive information to other attributes and thus benefit the classification task. Such a strategy can minimize the information lost, therefore is able to maximize the classification accuracy. Especially for the dataset contains hidden interactions among attributes. This paper proposes a feature selection methodology from a new angle that selects not only the relevant features, but also targeting at the potentially useful false irrelevant attributes by measuring their supportive importance to other attributes. The empirical results validate the hypothesis by demonstrating that the proposed approach outperforms most of the state-of-the-art filter based feature selection methods.

Based on Improved Genetic Algorithm for Task Scheduling of Heterogeneous Multi-Core Processor

2014 ◽  
Vol 1030-1032 ◽  
pp. 1671-1675
Author(s):  
Yue Qiu ◽  
Jing Feng Zang
Keyword(s):  
Genetic Algorithm ◽  
Task Scheduling ◽  
Execution Time ◽  
Scheduling Algorithm ◽  
Experimental Results ◽  
Initial Population ◽  
Improved Genetic Algorithm ◽  
High Quality ◽  
Multi Core Processor ◽  
Better Than

This paper puts forward an improved genetic scheduling algorithm in order to improve the execution efficiency of task scheduling of the heterogeneous multi-core processor system and give full play to its performance. The attribute values and the high value of tasks were introduced to structure the initial population, randomly selected a method with the 50% probability to sort for task of individuals of the population, thus to get high quality initial population and ensured the diversity of the population. The experimental results have shown that the performance of the improved algorithm was better than that of the traditional genetic algorithm and the HEFT algorithm. The execution time of tasks was reduced.

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