SLC: Symbolic Scheduling for Executing Parameterized Task Graphs on Multiprocessors

Authors:
Michel Cosnard;Emmanuel Jeannot;Tao Yang
Affiliations:
-;-;-
Venue:
ICPP '99 Proceedings of the 1999 International Conference on Parallel Processing
Year:
1999

Citing 0
Cited 3

Compact DAG representation and its symbolic scheduling

Journal of Parallel and Distributed Computing
Performance Evaluation of Task Pools Based on Hardware Synchronization

Proceedings of the 2004 ACM/IEEE conference on Supercomputing
A dynamic and reliability-driven scheduling algorithm for parallel real-time jobs executing on heterogeneous clusters

Journal of Parallel and Distributed Computing

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Abstract

Task graph scheduling has been found effective in performance prediction and optimization of parallel applications. A number of static scheduling algorithms have been proposed for task graph execution on distributed memory machines. Such an approach cannot be adapted to changes in values of program parameters and the number of processors and also it cannot handle large task graphs.In this paper, we model parallel computation using parameterized task graphs which represent coarse-grain parallelism independent of the problem size. We present a scheduling algorithm for a parameterized task graph which first derives symbolic linear clusters and then assigns task clusters to processors. The runtime system executes clusters on each processor in a multi-threaded fashion. We evaluate our method using various compute-intensive kernels that can be found in scientific applications.