Relevant bibliographies by topics / Dynamic Partitioned Scheduling

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Academic literature on the topic 'Dynamic Partitioned Scheduling'

Author: Grafiati
Published: 6 September 2023

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Journal articles on the topic "Dynamic Partitioned Scheduling"

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Wirawan Wijiutomo, Catur, Bambang Riyanto Trilaksono, and Achmad Imam Kistijantoro. "Fault Tolerant Dynamic Scheduling on Real Time Hierarchical System: Proposals for Fault Tolerant Mechanism on Safety-Critical System." International Journal of Engineering & Technology 7, no. 4.44 (December 1, 2018): 99. http://dx.doi.org/10.14419/ijet.v7i4.44.26871.

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The paradigm changes from federated architecture to integrated architecture in the real time system introduces a partitioned system to ensure fault isolation and for scheduling the hierarchy scheduling at the global level between partition and local in partition. Integrated architecture based on partitioned system with hierarchical scheduling is referred as real time hierarchical system which is a solution to increase efficiency in terms of hardware cost and size. This approach increasing the complexity of the integration process including the handling of faults. In this paper the authors describe a proposal with three components for dealing with fault tolerant in real time hierarchical systems by handling fault in task level, partition level and distributed level. The contribution of this proposal is the mechanism for building fault tolerant system on real time hierarchical system.
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Baruah, Sanjoy K., and Nathan Wayne Fisher. "The partitioned dynamic-priority scheduling of sporadic task systems." Real-Time Systems 36, no. 3 (April 25, 2007): 199–226. http://dx.doi.org/10.1007/s11241-007-9022-5.

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Sheikh, Saad Zia, and Muhammad Adeel Pasha. "A Dynamic Cache-Partition Schedulability Analysis for Partitioned Scheduling on Multicore Real-Time Systems." IEEE Letters of the Computer Society 3, no. 2 (July 1, 2020): 46–49. http://dx.doi.org/10.1109/locs.2020.3013660.

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Mascitti, Agostino, Tommaso Cucinotta, Mauro Marinoni, and Luca Abeni. "Dynamic partitioned scheduling of real-time tasks on ARM big.LITTLE architectures." Journal of Systems and Software 173 (March 2021): 110886. http://dx.doi.org/10.1016/j.jss.2020.110886.

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DIESSEL, OLIVER, and HOSSAM ELGINDY. "ON DYNAMIC TASK SCHEDULING FOR FPGA-BASED SYSTEMS." International Journal of Foundations of Computer Science 12, no. 05 (October 2001): 645–69. http://dx.doi.org/10.1142/s0129054101000709.

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The development of FPGAs that can be programmed to implement custom circuits by modifying memory has inspired researchers to investigate how FPGAs can be used as a computational resource in systems designed for high performance applications. When such FPGA–based systems are composed of arrays of chips or chips that can be partially reconfigured, the programmable array space can be partitioned among several concurrently executing tasks. If partition sizes are adapted to the needs of tasks, then array resources become fragmented as tasks with varying requirements are processed. Tasks may end up waiting despite their being sufficient, albeit fragmented resources available. We examine the problem of repartitioning the system (rearranging a subset of the executing tasks) at run–time in order to allow waiting tasks to enter the system sooner. In this paper, we introduce the problems of identifying and scheduling feasible task rearrangements when tasks are moved by reloading. It is shown that both problems are NP–complete. We develop two very different heuristic approaches to finding and scheduling suitable rearrangements. The first method, known as Local Repacking, attempts to minimize the size of the subarray needing rearrangement. Candidate subarrays are repacked using known bin packing algorithms. Task movements are scheduled so as to minimize delays to their execution. The second approach, called Ordered Compaction, constrains the movements of tasks in order to efficiently identify and schedule feasible rearrangements. The heuristics are compared by time complexity and resulting system performance on simulated task sets. The results indicate that considerable scheduling advantages are to be gained for acceptable computational effort. However, the benefits may be jeopardized by delays to moving tasks when the average cost of reloading tasks becomes significant relative to task service periods. We indicate directions for future research to mitigate the cost of moving executing tasks.
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Mahmood, Basharat, Naveed Ahmad, Majid Iqbal Khan, and Adnan Akhunzada. "Dynamic Priority Real-Time Scheduling on Power Asymmetric Multicore Processors." Symmetry 13, no. 8 (August 13, 2021): 1488. http://dx.doi.org/10.3390/sym13081488.

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The use of real-time systems is growing at an increasing rate. This raises the power efficiency as the main challenge for system designers. Power asymmetric multicore processors provide a power-efficient platform for building complex real-time systems. The utilization of this efficient platform can be further enhanced by adopting proficient scheduling policies. Unfortunately, the research on real-time scheduling of power asymmetric multicore processors is in its infancy. In this research, we have addressed this problem and added new results. We have proposed a dynamic-priority semi-partitioned algorithm named: Earliest-Deadline First with C=D Task Splitting (EDFwC=D-TS) for scheduling real-time applications on power asymmetric multicore processors. EDFwC=D-TS outclasses its counterparts in terms of system utilization. The simulation results show that EDFwC=D-TS schedules up to 67% more tasks with heavy workloads. Furthermore, it improves the processor utilization up to 11% and on average uses 14% less cores to schedule the given workload.
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Li, Xiao Feng, Peng Fan, Xiao Hua Liu, Xing Chao Wang, Chuan Hu, Chun Xiang Liu, and Shi Guang Bie. "Parallel Rendering Strategies for 3D Emulational Scene of Live Working." Applied Mechanics and Materials 457-458 (October 2013): 1021–27. http://dx.doi.org/10.4028/www.scientific.net/amm.457-458.1021.

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Because of abundant deep scene nodes in 3D emulational scene of live working, the existing three-dimensional scene data organization methods and rendering strategies have many flaws, such as the jumping of rendering and the delay of interactive response. A real-time rendering method for huge amount of urban data was presented utilizing the techniques such as identifying model that is based on multi-grid block partition, thread pool, caching and real time external memory scheduling algorithms. The whole scene was partitioned into blocks of different size and the blocks were arranged with multi-grid which is related to model ID and tile ID to accelerate model scheduling. Fast clipping was achieved through the nailing of position and direction of block-based view frustum, and touching task of data downloading off into thread pool executed in background which achieve the dynamic data loading and parallelism of three-dimensional scene rendering. To solve the choke point at computer hardware, in-out memory scheduling algorithms are adopted to eliminate invisible scene models and recycle dirty data in memory. Experimental results showed that the method is very efficient and suitable for applications in massive urban models rendering and interactive walkthrough.
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BANERJEE, AYAN, and EMMANOUEL (MANOS) VARVARIGOS. "A DYNAMIC SCHEDULING COMMUNICATION PROTOCOL AND ITS ANALYSIS FOR HYPERCUBE NETWORKS." International Journal of Foundations of Computer Science 09, no. 01 (March 1998): 39–56. http://dx.doi.org/10.1142/s0129054198000064.

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We propose a new protocol for one-to-one communication in multiprocessor networks, which we call the Dynamic Scheduling Communication (or DSC) protocol. In the DSC protocol, the capacity of a link is partitioned into two channels: a data channel, used to transmit packets, and a control channel used to make reservations. We initially describe the DSC protocol and the data structures needed to implement it for a general network topology. We then analyze the steady-state throughput of the DSC protocol for random node-to-node communication in a hypercube topology. The analytical results obtained are in very close agreement with corresponding simulation results. For the hypercube topology, and under the same set of assumptions on the node architecture and the routing algorithm used, the DSC protocol is found to achieve higher throughput than packet switching, provided that the size of the network is sufficiently large. We also investigate the relationship between the achievable throughput and the fraction of network capacity dedicated to the control channel, and present a method to select this fraction so as to optimize throughput.
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Zhang, Qiushi, Jian Zhao, Xiaoyu Wang, Li Tong, Hang Jiang, and Jinhui Zhou. "Distribution Network Hierarchically Partitioned Optimization Considering Electric Vehicle Orderly Charging with Isolated Bidirectional DC-DC Converter Optimal Efficiency Model." Energies 14, no. 6 (March 14, 2021): 1614. http://dx.doi.org/10.3390/en14061614.

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The access of large-scale electric vehicles (EVs) will increase the network loss of medium voltage distribution network, which can be alleviated by adjusting the network structure and orderly charging for EVs. However, it is difficult to accurately evaluate the charging efficiency in the orderly charging of electric vehicle (EV), which will cause the scheduling model to be insufficiently accurate. Therefore, this paper proposes an EV double-layer scheduling model based on the isolated bidirectional DC–DC (IBDC) converter optimal efficiency model, and establishes the hierarchical and partitioned optimization model with feeder–branch–load layer. Firstly, based on the actual topology of medium voltage distribution network, a dynamic reconfiguration model between switching stations is established with the goal of load balancing. Secondly, with the goal of minimizing the branch layer network loss, a dynamic reconstruction model under the switch station is established, and the chaotic niche particle swarm optimization is proposed to improve the global search capability and iteration speed. Finally, the power transmission loss model of IBDC converter is established, and the optimal phase shift parameter is determined to formulate the double-layer collaborative optimization operation strategy of electric vehicles. The example verifies that the above model can improve the system load balancing degree and reduce the operation loss of medium voltage distribution network.
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Shaheen, Anwar, and Sundar kumar. "Efficient Task Scheduling of Virtual Machines using Novel Spectral Partitioning and Differential Evaluation Algorithm." International Journal of Advances in Soft Computing and its Applications 14, no. 1 (March 28, 2022): 160–75. http://dx.doi.org/10.15849/ijasca.220328.11.

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Abstract Task-scheduling is a major challenge in cloud computing environment that degrades the performance of the system. To enhance the performance of the system, an effective task-scheduling algorithm is needed. Hence an effective task-partitioning and taskscheduling algorithm is introduced for enhancing the system performance. To create resources (datacentre, broker, Virtual Machine - VM and cloudlet) in a dynamic way through the use of CloudSim. In addition, this study intended to perform taskpartitioning and task-scheduling in an effective manner by utilizing the novel spectral partitioning - (SP) and differential evaluation algorithm - (DEA). At first, the task and datacentre is initialized. Subsequently, task-partitioning is performed using the novel SP. It includes a series of steps in which a Laplacian matrix is computed initially. Then based on the Eigen-values and Eigen-vectors of the Laplacian matrix the tasks are partitioned. Followed by this, taskscheduling is performed with the employment of proposed novel DEA. The process comprise the following series of steps such as threshold calculation, mutation, crossover, selection and knee solution for achieving efficient task-partitioning and scheduling. The performance of the proposed system is evaluated by comparing it with other traditional methods. And validated in terms of service cost, load balancing, makespan and energy consumption. The results proved the efficacy of the introduced system. The overall results obtained from comparative analysis also reveal that proposed method outperformed other traditional techniques thereby accomplishing effective task scheduling of VMs in cloud computing environment. Keywords: Cloud computing environment, Virtual Machines, Task Scheduling, Novel Spectral Partitioning and Differential Evaluation Algorithm.
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Conference papers on the topic "Dynamic Partitioned Scheduling"

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Hobbs, Clara, Zelin Tong, and James H. Anderson. "Optimal soft real-time semi-partitioned scheduling made simple (and dynamic)." In the 27th International Conference. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3356401.3356402.

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Mascitti, Agostino, and Tommaso Cucinotta. "Dynamic Partitioned Scheduling of Real-Time DAG Tasks on ARM big.LITTLE Architectures*." In RTNS'2021: 29th International Conference on Real-Time Networks and Systems. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3453417.3453442.

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"A FORMAL METHOD FOR SCHEDULING ANALYSIS OF A PARTITIONED MULTIPROCESSOR SYSTEM - Dynamic Priority Time Petri Nets." In International Conference on Pervasive and Embedded Computing and Communication Systems. SciTePress - Science and and Technology Publications, 2012. http://dx.doi.org/10.5220/0003809103170326.

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Silva, Fabricio Alves Barbosa da, and Isaac D. Scherson. "Concurrent Gang: Towards a Flexible and Scalable Gang Scheduler." In International Symposium on Computer Architecture and High Performance Computing. Sociedade Brasileira de Computação, 1999. http://dx.doi.org/10.5753/sbac-pad.1999.19796.

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Gang scheduling has been widely used as a practical solution to the dynamic parallel job scheduling problem. Parallel tasks of a job are scheduled for simultaneous execution on a partition of a parallel computer. Gang Scheduling has many advantages, such as responsiveness, efficient sharing of resources and ease of programming. However, there are two major problems associated with gang scheduling: scalability and the decision of what to do when a task blocks. In this paper we propose a class of scheduling policies, dubbed Concurrent Gang, that is a generalization of gang-scheduling, and allows for the flexible simultaneous scheduling of multiple parallel jobs with different characteristics. Besides that, scalability in Concurrent Gang is achieved through the use of a global clock that coordinates the gang scheduler among different processors.
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Tene, Matei, Michael Sekachev, Daniel de Brito Dias, and Matthew D. E. Szyndel. "Graphics Processing Unit Performance Scalability Study on a Commercial Black-Oil Reservoir Simulator." In SPE Reservoir Simulation Conference. SPE, 2023. http://dx.doi.org/10.2118/212183-ms.

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Abstract Commercial reservoir simulators have traditionally been optimized for distributed parallel execution on Central Processing Units (CPUs). Recent advances in Graphics Processing Units (GPUs) have led to the development of GPU-native simulators and triggered a shift towards a hardware-agnostic design in existing CPU solutions. For the latter, the suite of algorithms and data structures employed for a given computation are implemented for each target device. This results in a hybrid approach, where some simulator components inherently expose enough instruction parallelism or memory bandwidth requirements to warrant running on the GPU, while others are more suitable for the CPU. This paper examines the performance characteristics of a commercial black-oil reservoir simulator, which was recently extended with GPU support. Each simulation case will distribute load on the various modules in a reservoir simulator differently, depending on the target physical properties and the forecasted data desired. To assess this, the scalability of the simulator is measured in detail using the CPU and GPU, for components where both implementations are available, focusing on time spent during model initialization, property calculation, linearization, solver, field management and reporting. This is done using test cases which stress the simulator across several axes: grid resolution, different petrophysical property distributions, well count and the volume of reported data. The synthetic models which form the basis for these studies were designed to represent realistic reservoir engineering scenarios. The results show that a static partition between CPU- and GPU-assigned tasks, as employed by default in the simulator, is performant for scenarios where the work dedicated to grid cell properties and linear solution vastly outnumbers the effort spent resolving well or aquifer connections, field management and reporting. This is expected for typical simulation cases. However, when one of the latter aspects becomes dominant, the balance can shift, leading to suboptimal hardware utilization. In conclusion, if performance across all possible inputs is to be maintained, then a fully-CPU-and-GPU-capable simulator is needed, employing a dynamic scheduling strategy, where the runtime data locality, volume and parallelism of the corresponding computations are all considered when determining the target device for each operation. To the authors’ knowledge, a study on the scalability of a commercial reservoir simulator, across two different hardware architectures, has not previously been conducted to this level of detail. The results on realistic models are presented in the hope that they will contribute to the discussion surrounding the benefits of modern computing hardware for reservoir simulation and help drive deployment and design decisions for existing and future developments in both the commercial and academic spheres.
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