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» Fast performance prediction for periodic task systems
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HPCC
2007
Springer
15 years 9 months ago
An Exploration of Performance Attributes for Symbolic Modeling of Emerging Processing Devices
Vector, emerging (homogenous and heterogeneous) multi-core and a number of accelerator processing devices potentially offer an order of magnitude speedup for scientific application...
Sadaf R. Alam, Nikhil Bhatia, Jeffrey S. Vetter
ICML
1994
IEEE
15 years 9 months ago
A Modular Q-Learning Architecture for Manipulator Task Decomposition
Compositional Q-Learning (CQ-L) (Singh 1992) is a modular approach to learning to performcomposite tasks made up of several elemental tasks by reinforcement learning. Skills acqui...
Chen K. Tham, Richard W. Prager
ICPADS
1998
IEEE
15 years 10 months ago
Symbolic Partitioning and Scheduling of Parameterized Task Graphs
The DAG-based task graph model has been found effective in scheduling for performance prediction and optimization of parallel applications. However the scheduling complexity and s...
Michel Cosnard, Emmanuel Jeannot, Tao Yang
APCCM
2008
15 years 7 months ago
Making Workflows Context-aware: A Way to Support Knowledge-intensive Tasks
In business processes, knowledge-intensive tasks are ones in which the people performing such tasks are involved in a fair degree of uncertainty. These people are required to appl...
Mitra Heravizadeh, David Edmond
DATE
2010
IEEE
111views Hardware» more  DATE 2010»
15 years 11 months ago
Evaluation of runtime task mapping heuristics with rSesame - a case study
Abstract—rSesame is a generic modeling and simulation framework which can explore and evaluate reconfigurable systems at the early design stages. The framework can be used to ex...
Kamana Sigdel, Mark Thompson, Carlo Galuzzi, Andy ...