Scheduling precedence graphs in systems with interprocessor communication times
SIAM Journal on Computing
Models of machines and computation for mapping in multicomputers
ACM Computing Surveys (CSUR)
Optimal use of mixed task and data parallelism for pipelined computations
Journal of Parallel and Distributed Computing
CASCH: A Tool for Computer-Aided Scheduling
IEEE Concurrency
A New Model for Static Mapping of Parallel Applications with Task and Data Parallelism
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Clustering and Reassignment-Based Mapping Strategy for Message-Passing Architectures
IPPS '98 Proceedings of the 12th. International Parallel Processing Symposium on International Parallel Processing Symposium
Bounds on the Number of Processors and Time for Multiprocessor Optimal Schedules
IEEE Transactions on Computers
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The mapping of parallel applications constitutes a difficult problem for which very few practical tools are available. AMEEDA has been developed in order to overcome the lack of a general-purpose mapping tool. The automatic services provided in AMEEDA include instrumentation facilities, parameter extraction modules and mapping strategies. With all these services, and a novel graph formalism called TTIG, users can apply different mapping strategies to the corresponding application through an easy-to-use GUI, and run the application on a PVM cluster using the desired mapping.