A Survey of Pipelined Workflow Scheduling: Models and Algorithms

International audienceA large class of applications need to execute the same workflow on different data sets of identical size. Efficient execution of such applications necessitates intelligent distribution of the application components and tasks on a parallel machine, and the execution can be orchestrated by utilizing task-, data-, pipelined-, and/or replicated-parallelism. The scheduling problem that encompasses all of these techniques is called pipelined workflow scheduling, and it has been widely studied in the last decade. Multiple models and algorithms have flourished to tackle various programming paradigms, constraints, machine behaviors or optimization goals. This paper surveys the field by summing up and structuring known results and approaches

Formal and Informal Methods for Multi-Core Design Space Exploration

We propose a tool-supported methodology for design-space exploration for embedded systems. It provides means to define high-level models of applications and multi-processor architectures and evaluate the performance of different deployment (mapping, scheduling) strategies while taking uncertainty into account. We argue that this extension of the scope of formal verification is important for the viability of the domain.Comment: In Proceedings QAPL 2014, arXiv:1406.156

A Genetic Algorithm to Schedule Workflow Collections on a SOA-Grid with Communication Costs

International audienceIn this paper we study the problem of scheduling a collection of workflows, identical or not, on a SOA grid. A workflow (job) is represented by a directed acyclic graph (DAG) with typed tasks. All of the grid hosts are able to process a set of task types with unrelated processing costs and are able to transmit files through communication links for which the communication times are not negligible. The goal is to minimize the maximum completion time (makespan) of the workflows. To solve this problem we propose a genetic approach. The contributions of this paper are both the design of a Genetic Algorithm taking the communication costs into account and the performance analysis

Iso-Level CAFT: How to Tackle the Combination of Communication Overhead Reduction and Fault Tolerance Scheduling

To schedule precedence task graphs in a more realistic framework, we introduce an efficient fault tolerant scheduling algorithm that is both contention-aware and capable of supporting $\varepsilon$ arbitrary fail-silent (fail-stop) processor failures. The design of the proposed algorithm which we call Iso-Level CAFT, is motivated by (i) the search for a better load-balance and (ii) the generation of fewer communications. These goals are achieved by scheduling a chunk of ready tasks simultaneously, which enables for a global view of the potential communications. Our goal is to minimize the total execution time, or latency, while tolerating an arbitrary number of processor failures. Our approach is based on an active replication scheme to mask failures, so that there is no need for detecting and handling such failures. Major achievements include a low complexity, and a drastic reduction of the number of additional communications induced by the replication mechanism. The experimental results fully demonstrate the usefulness of Iso-Level~CAFT

Suitable task allocation in intelligent systems for assistive environments

The growing need of technological assistance to provide support to people with special needs demands for systems more and more efficient and with better performances. With this aim, this work tries to advance in a multirobot platform that allows the coordinated control of different agents and other elements in the environment to achieve an autonomous behavior based on the user’s needs or will. Therefore, this environment is structured according to the potentiality of each agent and elements of this environment and of the dynamic context, to generate the adequate actuation plans and the coordination of their execution.Peer ReviewedPostprint (author's final draft

Fault Tolerant Scheduling of Precedence Task Graphs on Heterogeneous Platforms

Fault tolerance and latency are important requirements in several applications which are time critical in nature: such applications require guaranties in terms of latency, even when processors are subject to failures. In this paper, we propose a fault tolerant scheduling heuristic for mapping precedence task graphs on heterogeneous systems. Our approach is based on an active replication scheme, capable of supporting $\varepsilon$ arbitrary fail-silent (fail-stop) processor failures, hence valid results will be provided even if $\varepsilon$ processors fail. We focus on a bi-criteria approach, where we aim at minimizing the latency given a fixed number of failures supported in the system, or the other way round. Major achievements include a low complexity, and a drastic reduction of the number of additional communications induced by the replication mechanism. Experimental results demonstrate that our heuristics, despite their lower complexity, outperform their direct competitor, the FTBAR scheduling algorithm[8].La tolérance aux pannes et la latence sont deux critères importants pour plusieurs applications qui sont critiques par nature. Ce type d’applications exige des garanties en terme de temps de latence, même lorsque les processeurs sont sujets aux pannes. Dans ce rapport, nous proposons une heuristique tolérante aux pannes pour l’ordonnancement de graphes de tâches sur des systèmes hétérogènes. Notre approche est basée sur un mécanisme de réplication active, capable de supporter " pannes arbitraires de type silence sur défaillance. En d’autres termes, des résultats valides seront fournis même si " processeurs tombent en panne. Nous nous concentrons sur une approche bi-critère, où nous avons pour objectif de minimiser le temps de latence pour un nombre donné (fixé) de pannes tolérées dans le système, ou l’inverse. Les principales contributions incluent une faible complexité en temps d’exécution, et une réduction importante du nombre de communications induites par le mécanisme de réplication.Les résultats expérimentaux montrent que notre algorithme, en dépit de sa faible complexité temporelle, est meilleur que son direct compétiteur,l’algorithme FTBA

A Bi-Criteria Algorithm for Scheduling Parallel Task Graphs on Clusters

International audienceApplications structured as parallel task graphs exhibit both data and task parallelism, and arise in many domains. Scheduling these applications on parallel platforms has been a long-standing challenge. In the case of a single homogeneous cluster, most of the existing algorithms focus on the reduction of the application completion time (makespan). But in presence of resource managers such as batch schedulers and due to accentuated pressure on energy concerns, the produced schedules also have to be efficient in terms of resource usage. In this paper we propose a novel bi-criteria algorithm, called biCPA, able to optimize these two performance metrics either simultaneously or separately. Using simulation over a wide range of experimental scenarios, we find that biCPA leads to better results than previously published algorithms

Jedule: A Tool for Visualizing Schedules of Parallel Applications

International audienceTask scheduling is one of the most prominent problems in the era of parallel computing. We find scheduling algorithms in every domain of computer science, e.g., mapping multiprocessor tasks to clusters, mapping jobs to grid resources, or mapping fine-grained tasks to cores of multicore processors. Many tools exist that help understand or debug an application by presenting visual representations of a certain program run, e.g., visualizations of MPI traces. However, often developers want to get a global and abstract view of their schedules first. In this paper we introduce Jedule, a tool dedicated to visualize schedules of parallel applications. We demonstrate the effectiveness of Jedule by showing how it helped analyzing problems in several case studies