A semi-static approach to mapping dynamic iterative tasks onto heterogeneous computing systems

Kwok, Yue Kuen; Maciejewski, Anthony A.; Siegel, Howard Jay; Ahmad, Ishfaq; Ghafoor, Arif

doi:10.1016/j.jpdc.2005.06.015

Cited by 36 publications

(39 citation statements)

References 48 publications

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“…A semi-static approach to mapping dynamic iterative tasks onto heterogeneous computing system [1], implement and evaluate a semi-static methodology involving the on-line use of off-line-derived mappings. The off-line phase is based on a genetic algorithm (GA) to generate high-quality mappings for a range of values for the dynamic parameters.…”

Section: Related Workmentioning

confidence: 99%

TRP Maximization Technique based Efficient Scheduling in Grid Environment

Indhumathi¹

2018

IJSRCSE

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-The problem of heterogeneous job scheduling in grid environment is well studied. Number of approaches considers different factors of resource and process in terms of completion, waiting and throughput. However, the methods suffer to achieve higher performance in scheduling in grid environment. To improve the performance, an efficient TRP maximization algorithm is presented in this paper. First, the method identifies list of processes and their required resource with their hold time. Based on the information obtained, a set of two hop sequences are generated for each resource available. For each two hop sequence, the method compute throughput maximization support, resource utilization maximization factor and process completion maximization factor. Using all these, a scheduling maximization support has been estimated. Based on the support measure a single one has been selected for each resource available. The same will be iterated for each level of scheduling and the method produces higher efficiency in scheduling. The performance of scheduling has been improved with less waiting time.

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Section: Related Workmentioning

confidence: 99%

TRP Maximization Technique based Efficient Scheduling in Grid Environment

Indhumathi¹

2018

IJSRCSE

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“…To check schedulability of a task chain, it is sufficient and necessary to test the individual end-to-end response times of all tasks belonging to that chain [73]. In [73], a technique for endto-end schedulability analysis is proposed, but it assumes a pipelined task execution pattern, where multiple jobs of the same task chain are executed simultaneously over different cores, but the simultaneous execution of more than one job of the same task is not allowed. When the execution pattern does not follow this scheme, meeting end-to-end deadlines can be checked by assigning an appropriate local deadline for each job in every chain.…”

Section: Proposed Approach 87mentioning

confidence: 99%

“…Otherwise, the most efficient multi-choice knapsack problem (MMKP) heuristics, listed in the brief survey earlier, have to be applied to identify the current mode on-line, as proposed in [73].…”

Section: On-line Stepsmentioning

confidence: 99%

“…A number of research activity aims at developing design-time (offline) heuristics to reduce the number of operating points, since the amount of possible scenarios is typically prohibitively high [89]. This Design Space Exploration (DSE) process can be carried out using classic heuristic techniques (including genetic algorithms [73,89,116], tabu search [115], simulated annealing [160], particle swarm optimization [103], etc. ), or with techniques for pruning the design space [107], performing statistical analysis for identifying potentially benefiting operating points, or use a priori knowledge of the target platform [14].…”

Section: Related Workmentioning

confidence: 99%

“…Then during run-time of that system, a run-time manager (RTM) chooses an appropriate operating point according to the available platform resources by solving an instance of multi-dimensional multi-choice knapsack problem (MMKP). Despite MMKP belongs to the NP-hard complexity class, there exists a number of light-weight greedy heuristics facilitating finding a quasi-optimal mapping during run-time [73]. Alternatively, in [104], there is a possibility of determining the current mode out of explicitly given set by observing some variables of the model.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

Dynamic Resource Allocation in Embedded, High-Performance and Cloud Computing

Indrusiak

Dziurzański

Singh

2016

Dynamic Resource Allocation in Embedded, High-Performance and Cloud Computing

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The "River Publishers Series in Information Science and Technology" covers research which ushers the 21st Century into an Internet and multimedia era. Multimedia means the theory and application of filtering, coding, estimating, analyzing, detecting and recognizing, synthesizing, classifying, recording, and reproducing signals by digital and/or analog devices or techniques, while the scope of "signal" includes audio, video, speech, image, musical, multimedia, data/content, geophysical, sonar/radar, bio/medical, sensation, etc. Networking suggests transportation of such multimedia contents among nodes in communication and/or computer networks, to facilitate the ultimate Internet.Theory, technologies, protocols and standards, applications/services, practice and implementation of wired/wireless networking are all within the scope of this series. Based on network and communication science, we further extend the scope for 21st Century life through the knowledge in robotics, machine learning, embedded systems, cognitive science, pattern recognition, quantum/biological/molecular computation and information processing, biology, ecology, social science and economics, user behaviors and interface, and applications to health and society advance.Books published in the series include research monographs, edited volumes, handbooks and textbooks. The books provide professionals, researchers, educators, and advanced students in the field with an invaluable insight into the latest research and developments.

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An evolutionary game algorithm for grid resource allocation under bounded rationality

Cheng

2009

Concurrency and Computation

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SUMMARYResource allocation cannot reach equilibrium in one-off game in grid environment because of the bounded rationality of the users. To address this issue, an evolutionary game algorithm for grid resource allocation is proposed in this paper. The evolutionary game theory is introduced to study the selection process of user strategy from the dynamic viewpoint. Firstly, the problem of multiple users competing for a common resource is formulated as a symmetric game. Secondly, replicated dynamic mechanism is used to produce the evolutionary stable point that leads to a satisfied allocation scenario. Finally, the relationships among the evolutionary stable point, valuation functions, and convergence time are discussed in detail. The results of the experiments show that the proposed evolutionary game algorithm is convergent and generates better utility results compared with the classical game algorithm.

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A semi-static approach to mapping dynamic iterative tasks onto heterogeneous computing systems

Cited by 36 publications

References 48 publications

TRP Maximization Technique based Efficient Scheduling in Grid Environment

TRP Maximization Technique based Efficient Scheduling in Grid Environment

Dynamic Resource Allocation in Embedded, High-Performance and Cloud Computing

An evolutionary game algorithm for grid resource allocation under bounded rationality

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