Data networks
A tight analysis of the greedy algorithm for set cover
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
Flow and stretch metrics for scheduling continuous job streams
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Open Shop Scheduling to Minimize Finish Time
Journal of the ACM (JACM)
On Preemptive Scheduling of Unrelated Parallel Processors by Linear Programming
Journal of the ACM (JACM)
Parallelization of local BLAST service on workstation clusters
Future Generation Computer Systems
Approximation schemes for preemptive weighted flow time
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Improved algorithms for stretch scheduling
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Scheduling Divisible Loads in Parallel and Distributed Systems
Scheduling Divisible Loads in Parallel and Distributed Systems
Computers and Intractability; A Guide to the Theory of NP-Completeness
Computers and Intractability; A Guide to the Theory of NP-Completeness
Bandwidth sharing: objectives and algorithms
IEEE/ACM Transactions on Networking (TON)
Scheduling Dependent Tasks with Different Arrival Times to Meet Deadlines
Proceedings of the International Workshop organized by the Commision of the European Communities on Modelling and Performance Evaluation of Computer Systems
Scheduling Distributed Applications: the SimGrid Simulation Framework
CCGRID '03 Proceedings of the 3st International Symposium on Cluster Computing and the Grid
Online Scheduling to Minimize Average Stretch
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
New algorithms and metrics for scheduling
New algorithms and metrics for scheduling
Approximation Algorithms for Average Stretch Scheduling
Journal of Scheduling
Off-Line Scheduling of Divisible Requests on an Heterogeneous Collection of Databanks
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 1 - Volume 02
Complexity of preemptive minsum scheduling on unrelated parallel machines
Journal of Algorithms
Minimizing the stretch when scheduling flows of biological requests
Proceedings of the eighteenth annual ACM symposium on Parallelism in algorithms and architectures
Handbook on Scheduling: Models and Methods for Advanced Planning (International Handbooks on Information Systems)
The complexity of mean flow time scheduling problems with release times
Journal of Scheduling
Resource Allocation Using Virtual Clusters
CCGRID '09 Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid
Resource allocation algorithms for virtualized service hosting platforms
Journal of Parallel and Distributed Computing
Adaptive statistical scheduling of divisible workloads in heterogeneous systems
Journal of Scheduling
On the utility of DVFS for power-aware job placement in clusters
Euro-Par'11 Proceedings of the 17th international conference on Parallel processing - Volume Part I
Energy-aware service allocation
Future Generation Computer Systems
Optimizing the stretch of independent tasks on a cluster: From sequential tasks to moldable tasks
Journal of Parallel and Distributed Computing
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In this paper, we consider the problem of scheduling distributed biological sequence comparison applications. This problem lies in the divisible load framework with negligible communication costs. Thus far, very few results have been proposed for this model. We discuss and select relevant metrics for this framework: namely max-stretch and sum-stretch. We explain the relationship between our model and the preemptive single processor case, and we show how to extend algorithms that have been proposed in the literature for the single processor model to the divisible multi-processor problem domain. We recall known results on closely related problems, we show how to minimize the max-stretch on unrelated machines either in the divisible load model or with preemption, we derive new lower bounds on the competitive ratio of any online algorithm, we present new competitiveness results for existing algorithms, and we develop several new online heuristics. We also address the Pareto optimization of max-stretch. Then, we extensively study the performance of these algorithms and heuristics under realistic scenarios. Our study shows that all previously proposed guaranteed heuristics for max-stretch for the single processor model are inefficient in practice. In contrast, we show that our online algorithms based on linear programming are in practice near-optimal solutions for max-stretch. Our study also clearly suggests heuristics that are efficient for both metrics, although a combined optimization is in theory not possible in the general case.