Malleable task-graph scheduling with a practical speed-up model

Scientific workloads are often described by Directed Acyclic task Graphs.Indeed, DAGs represent both a model frequently studied in theoretical literature and the structure employed by dynamic runtime schedulers to handle HPC applications. A natural problem is then to compute a makespan-minimizing schedule of a given graph. In this paper, we are motivated by task graphs arising from multifrontal factorizations of sparsematrices and therefore work under the following practical model. We focus on malleable tasks (i.e., a single task can be allotted a time-varying number of processors) and specifically on a simple yet realistic speedup model: each task can be perfectly parallelized, but only up to a limited number of processors. We first prove that the associated decision problem of minimizing the makespan is NP-Complete. Then, we study a widely used algorithm, PropScheduling, under this practical model and propose a new strategy GreedyFilling. Even though both strategies are 2-approximations, experiments on real and synthetic data sets show that GreedyFilling achieves significantly lower makespans

Idle block based methods for cloud workflow scheduling with preemptive and non-preemptive tasks

[EN] Complex workflow applications are widely used in scientific computing and economic analysis, which commonly include both preemptive and non-preemptive tasks. Cloud computing provides a convenient way for users to access different resources based on the ¿pay-as-you-go¿ model. However, different resource renting alternatives (reserved, on-demand or spot) are usually provided by the service provider. The spot instances provide a dynamic and cheaper alternative comparing to the on-demand one. However, failures often occur due to the fluctuations of the price of the instance. It is a big challenge to determine the appropriate amount of spot and on-demand resources for workflow applications with both preemptive and non-preemptive tasks. In this paper, the workflow scheduling problem with both spot and on-demand instances is considered. The objective is to minimize the total renting cost under deadline constrains. An idle time block-based method is proposed for the considered problem. Different idle time block-based searing and improving strategies are developed to construct schedules for workflow applications. Schedules are improved by a forward and backward moving mechanism. Experimental and statistical results demonstrate the effectiveness of the proposed algorithm over a lot of tests with different sizes.This work is supported by the National Natural Science Foundation of China (No. 61572127, 61272377), the National Key Research and Development Program of China (No. 2017YFB1400800). Ruben Ruiz is partially supported by the Spanish Ministry of Economy and Competitiveness, under the project "SCHEYARD - Optimization of Scheduling Problems in Container Yards" (No. DPI2015-65895-R) financed by FEDER funds.Chen, L.; Li, X.; Ruiz García, R. (2018). Idle block based methods for cloud workflow scheduling with preemptive and non-preemptive tasks. Future Generation Computer Systems. 89:659-669. https://doi.org/10.1016/j.future.2018.07.037S6596698

Multi-agent scheduling on a single machine with max-form criteria

Author name used in this publication: T. C. E. ChengAuthor name used in this publication: C. T. Ng2007-2008 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Impact of AS6802 Synchronization Protocol on Time-Triggered and Rate-Constrained Traffic

TTEthernet is an Ethernet-based synchronized network technology compliant with the AFDX standard. It supports safety-critical applications by defining different traffic classes: Time-Triggered (TT), Rate-Constrained (RC), and Best-Effort traffic. The synchronization is managed through the AS6802 protocol, which defines so-called Protocol Control Frames (PCFs) to synchronize the local clock of each device. In this paper, we analyze the synchronization protocol to assess the impact of the PCFs on TT and RC traffic. We propose a method to decrease the impact of PCFs on TT and a new Network Calculus model to compute RC delay bounds with the influence of both PCF and TT traffic. We finish with a performance evaluation to i) assess the impact of PCFs, ii) show the benefits of our method in terms of reducing the impact of PCFs on TT traffic and iii) prove the necessity of taking the PCF traffic into account to compute correct RC worst-case delays and provide a safe system

Scheduling Periodical Multi-Stage Jobs With Fuzziness to Elastic Cloud Resources

© 2020 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.[EN] We investigate a workflow scheduling problem with stochastic task arrival times and fuzzy task processing times and due dates. The problem is common in many real-time and workflow-based applications, where tasks with fixed stage number and linearly dependency are executed on scalable cloud resources with multiple price options. The challenges lie in proposing effective, stable, and robust algorithms under stochastic and fuzzy tasks. A triangle fuzzy number-based model is formulated. Two metrics are explored: the cost and the degree of satisfaction. An iterated heuristic framework is proposed to periodically schedule tasks, which consists of a task collection and a fuzzy task scheduling phases. Two task collection strategies are presented and two task prioritization strategies are employed. In order to achieve a high satisfaction degree, deadline constraints are defined at both job and task levels. By designing delicate experiments and applying sophisticated statistical techniques, experimental results show that the proposed algorithm is more effective and robust than the two existing methods.This work was supported by the National Key Research and Development Program of China (No. 2017YFB1400800), the National Natural Science Foundation of China (Nos. 61672297, 61872077, and 61832004), the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (Grant No. 18KJB520039) and the National Science Foundation for Post-doctoral Scientists of China (Grant No. 2018M640510). Ruben Ruiz was partially supported by the Spanish Ministry of Science, Innovation, and Universities, under the project "OPTEP-Port Terminal Operations Optimization" (No. RTI2018-094940-B-I00) financed with FEDER funds. The authors would like to thank the anonymous reviewers for their valuable feedback on this work.Zhu, J.; Li, X.; Ruiz García, R.; Li, W.; Huang, H.; Zomaya, AY. (2020). Scheduling Periodical Multi-Stage Jobs With Fuzziness to Elastic Cloud Resources. IEEE Transactions on Parallel and Distributed Systems. 31(12):2819-2833. https://doi.org/10.1109/TPDS.2020.3004134S28192833311

Jackson's rule for one-machine scheduling : making a good heuristic better

Includes bibliographical references (leaves 21-22).by Leslie A. Hall and David B. Shmoys

Runtime support for load balancing of parallel adaptive and irregular applications

Applications critical to today\u27s engineering research often must make use of the increased memory and processing power of a parallel machine. While advances in architecture design are leading to more and more powerful parallel systems, the software tools needed to realize their full potential are in a much less advanced state. In particular, efficient, robust, and high-performance runtime support software is critical in the area of dynamic load balancing. While the load balancing of loosely synchronous codes, such as field solvers, has been studied extensively for the past 15 years, there exists a class of problems, known as asynchronous and highly adaptive , for which the dynamic load balancing problem remains open. as we discuss, characteristics of this class of problems render compile-time or static analysis of little benefit, and complicate the dynamic load balancing task immensely.;We make two contributions to this area of research. The first is the design and development of a runtime software toolkit, known as the Parallel Runtime Environment for Multi-computer Applications, or PREMA, which provides interprocessor communication, a global namespace, a framework for the implementation of customized scheduling policies, and several such policies which are prevalent in the load balancing literature. The PREMA system is designed to support coarse-grained domain decompositions with the goals of portability, flexibility, and maintainability in mind, so that developers will quickly feel comfortable incorporating it into existing codes and developing new codes which make use of its functionality. We demonstrate that the programming model and implementation are efficient and lead to the development of robust and high-performance applications.;Our second contribution is in the area of performance modeling. In order to make the most effective use of the PREMA runtime software, certain parameters governing its execution must be set off-line. Optimal values for these parameters may be determined through repeated executions of the target application; however, this is not always possible, particularly in large-scale environments and long-running applications. We present an analytic model that allows the user to quickly and inexpensively predict application performance and fine-tune applications built on the PREMA platform

Utilization of Buffers for Performance Evaluation of Local Area Network Protocols

This paper discusses the performance of traffic flow over Local Area Networks (LAN) utilizing buffers to avoid any irrelevant traffic that clusters the network using sniffer pro. The study applies buffer technology to filter out unnecessary information so the system captures only required information packets. Buffers that capture the protocols are identified. These are. Address Resolution Protocols (ARP), Internet Control Message Protocol (ICMP), Transmission Control Protocol (TCP), and User Datagram Protocol (UDP). The study identified to the user/analyzer of an Ethernet technology, how to isolate a cluster network problem, monitor network performance, and offer tips on how to correctly assess and fix network problems. The study provides detailed analysis of threshold gauges, errors, broadcasts, multicasts, packets, and many other facets of dashboard graph configurations thereby ensuring a successful network analysis. The study concludes by providing solutions to poor network performance affecting one user, several users, or an entire network