Supercompilers for parallel and vector computers
Supercompilers for parallel and vector computers
Parallel algorithms for shared-memory machines
Handbook of theoretical computer science (vol. A)
LogP: towards a realistic model of parallel computation
PPOPP '93 Proceedings of the fourth ACM SIGPLAN symposium on Principles and practice of parallel programming
Optimal broadcast and summation in the LogP model
SPAA '93 Proceedings of the fifth annual ACM symposium on Parallel algorithms and architectures
LogP: a practical model of parallel computation
Communications of the ACM
Designing and Building Parallel Programs: Concepts and Tools for Parallel Software Engineering
Designing and Building Parallel Programs: Concepts and Tools for Parallel Software Engineering
High Performance Compilers for Parallel Computing
High Performance Compilers for Parallel Computing
On Linear Schedules of Task Graphs for Generalized LogP-Machines
Euro-Par '97 Proceedings of the Third International Euro-Par Conference on Parallel Processing
Parallelization of Non-Simultaneous Iterative Methods for Systems of Linear Equations
CONPAR 94 - VAPP VI Proceedings of the Third Joint International Conference on Vector and Parallel Processing: Parallel Processing
An Approach to Machine-Independent Parallel Programming
CONPAR 94 - VAPP VI Proceedings of the Third Joint International Conference on Vector and Parallel Processing: Parallel Processing
On the Optimization by Redundancy Using an Extended LogP Model
APDC '97 Proceedings of the 1997 Advances in Parallel and Distributed Computing Conference (APDC '97)
Foundations for the integration of scheduling techniques into compilers for parallel languages
International Journal of Computational Science and Engineering
Optimal linear programming solutions for multiprocessor scheduling with communication delays
ICA3PP'12 Proceedings of the 12th international conference on Algorithms and Architectures for Parallel Processing - Volume Part I
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Usually, scheduling algorithms are designed for task-graphs. Task-graphs model oblivious algorithms, but not iterative algorithms where the number of iterations is unknown (e.g. while-loops). We generalize scheduling techniques known for oblivious algorithms to iterative algorithms. We prove bounds for the execution time of such algorithms in terms of the optimum.