Approximation algorithms for scheduling with a limited number of communications

International audienceWe consider the case of a UET tree and an unlimited number of processors. We give a 2-approximation algorithm for minimizing the total number of communications, when there are no communication delays. This algorithm allows us to design a 6-approximation algorithm for the makespan minimization problem when there are unit length communication delays and the processors are interconnected by a single bus. Finally, we compare our 6-approximation algorithm with other algorithms by simulations. We show that its mean performance is regular (around 1.25) and we explain, for certain cases, the performance of these algorithms by considering some parameters of the problem

Improved Mixed-Integer Programming Models for Multiprocessor Scheduling with Communication Delays

We revise existing and introduce new mixed-integer programming models for the Multiprocessor Scheduling Problem with Communication Delays. At first, we show how to provably reduce the number of product variables necessary to explicitly linearize the so-called packing formulation that contains bilinear terms. Then, we reveal that the feasible region of almost all existing formulations contains redundant solutions and formulate new constraints in order to exclude these. At the same time, by exploiting further structural properties, the models are improved concerning their size, strength, and modeling complexity. The discussion of these improvements leads to new much more compact formulations which are then experimentally compared with each other and with other formulations from the literature. We set up a realistic scenario with a preprocessing of the task graphs, delivering the gained information equally to all the tested models and evaluate not only running times but also the obtained lower and upper bounds on the makespan objective for unsolved instances of a large scale benchmark set

When Network Matters: Data Center Scheduling with Network Tasks

International audienceWe consider the placement of jobs inside a data center. Traditionally, this is done by a task orchestrator without taking into account network constraints. According to recent studies, network transfers represent up to 50% of the completion time of classical jobs. Thus, network resources must be considered when placing jobs in a data center. In this paper, we propose a new scheduling framework, introducing network tasks that need to be executed on network machines alongside traditional (CPU) tasks. The model takes into account the competition between communications for the network resources, which is not considered in the formerly proposed scheduling models with communication. Network transfers inside a data center can be easily modeled in our framework. As we show, classical algorithms do not efficiently handle a limited amount of network bandwidth. We thus propose new provably efficient algorithms with the goal of minimizing the makespan in this framework. We show their efficiency and the importance of taking into consideration network capacity through extensive simulations on workflows built from Google data center traces

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

Scheduling Series-Parallel Orders Subject to 0/1-Communication Delays

We consider the problem P}&;| prec},cij&;{0,1}|κ of scheduling jobs with arbitrary processing times on sufficiently many parallel processors subject to series-parallel precedence constraints and 0/1-communication delays in order to minimize a regular performance measure κ. Such schedules without processor restrictions are used for generating approximate solutions for a restricted number of processors