Complexity of scheduling parallel task systems
SIAM Journal on Discrete Mathematics
Approximate algorithms scheduling parallelizable tasks
SPAA '92 Proceedings of the fourth annual ACM symposium on Parallel algorithms and architectures
Handbook of Approximation Algorithms and Metaheuristics (Chapman & Hall/Crc Computer & Information Science Series)
A $\frac32$-Approximation Algorithm for Scheduling Independent Monotonic Malleable Tasks
SIAM Journal on Computing
An approximation algorithm for scheduling malleable tasks under general precedence constraints
ISAAC'05 Proceedings of the 16th international conference on Algorithms and Computation
Hierarchical scheduling for moldable tasks
Euro-Par'05 Proceedings of the 11th international Euro-Par conference on Parallel Processing
Scheduling malleable tasks with precedence constraints
Journal of Computer and System Sciences
Online optimization of busy time on parallel machines
TAMC'12 Proceedings of the 9th Annual international conference on Theory and Applications of Models of Computation
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Malleable tasks are a way of modelling jobs that can be parallelized to get a (usually sublinear) speedup. The best currently known approximation algorithms for scheduling malleable tasks with precedence constraints are a) a 2.62-approximation for certain classes of precedence constraints such as series-parallel graphs [1], and b) a 4.72-approximation for general graphs via linear programming [2]. We show that these rates are tight, i.e. there exist instances that achieve the upper bounds.