Algorithmic skeletons: structured management of parallel computation
Algorithmic skeletons: structured management of parallel computation
Structured development of parallel programs
Structured development of parallel programs
Allocating independent tasks to parallel processors: an experimental study
Journal of Parallel and Distributed Computing - Special issue on dynamic load balancing
Divisible task scheduling — concept and verification
Parallel Computing - Special issue on task scheduling problems for parallel and distributed systems
Adaptive performance prediction for distributed data-intensive applications
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
Future Generation Computer Systems - Special issue on metacomputing
The AppLeS parameter sweep template: user-level middleware for the grid
Proceedings of the 2000 ACM/IEEE conference on Supercomputing
Scheduling Divisible Loads in Parallel and Distributed Systems
Scheduling Divisible Loads in Parallel and Distributed Systems
Adaptive Computing on the Grid Using AppLeS
IEEE Transactions on Parallel and Distributed Systems
Grid programming: some indications where we are headed
Parallel Computing - Special issue: Advanced environments for parallel and distributed computing
High Performance Parametric Modeling with Nimrod/G: Killer Application for the Global Grid?
IPDPS '00 Proceedings of the 14th International Symposium on Parallel and Distributed Processing
An advanced environment supporting structured parallel programming in Java
Future Generation Computer Systems - Tools for program development and analysis
Scheduling divisible workloads on heterogeneous platforms
Parallel Computing - Parallel matrix algorithms and applications (PMAA '02)
Grid resource management: state of the art and future trends
Grid resource management: state of the art and future trends
The Grid 2: Blueprint for a New Computing Infrastructure
The Grid 2: Blueprint for a New Computing Infrastructure
Self adaptivity in Grid computing: Research Articles
Concurrency and Computation: Practice & Experience - Grid Performance
A Grid-Based Stochastic Simulation of Unitary and Membrane Ca^2+ Currents in Spherical Cells
CBMS '05 Proceedings of the 18th IEEE Symposium on Computer-Based Medical Systems
Multiround Algorithms for Scheduling Divisible Loads
IEEE Transactions on Parallel and Distributed Systems
An adaptive skeletal task farm for grids
Euro-Par'05 Proceedings of the 11th international Euro-Par conference on Parallel Processing
Flexible skeletal programming with eskel
Euro-Par'05 Proceedings of the 11th international Euro-Par conference on Parallel Processing
Pitfalls in parallel job scheduling evaluation
JSSPP'05 Proceedings of the 11th international conference on Job Scheduling Strategies for Parallel Processing
Adaptive structured parallelism for computational grids
Proceedings of the 12th ACM SIGPLAN symposium on Principles and practice of parallel programming
Adaptive statistical scheduling of divisible workloads in heterogeneous systems
Journal of Scheduling
A survey of algorithmic skeleton frameworks: high-level structured parallel programming enablers
Software—Practice & Experience - Focus on Selected PhD Literature Reviews in the Practical Aspects of Software Technology
Performance evaluation of MapReduce using full virtualisation on a departmental cloud
International Journal of Applied Mathematics and Computer Science - SPECIAL SECTION: Efficient Resource Management for Grid-Enabled Applications
Towards fully adaptive pipeline parallelism for heterogeneous distributed environments
ISPA'06 Proceedings of the 4th international conference on Parallel and Distributed Processing and Applications
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In this work, we introduce a self-adaptive task farm for computational grids which is based on a single-round scheduling algorithm called dynamic deal. In principle, the dynamic deal approach employs skeletal forecasting information to automatically instrument the task farm scheduling and determine the amount of work assigned to each worker at execution time, allowing the farm to adapt effectively to different load and network conditions in the grid. In practice, it uses self-generated predictive execution values and maps tasks onto the different nodes in a single-round. The effectiveness of this approach is illustrated with a computational biology parameter sweep in a non-dedicated departmental grid.