On communication latency in PRAM computations
SPAA '89 Proceedings of the first annual ACM symposium on Parallel algorithms and architectures
A bridging model for parallel computation
Communications of the ACM
LogP: towards a realistic model of parallel computation
PPOPP '93 Proceedings of the fourth ACM SIGPLAN symposium on Principles and practice of parallel programming
Proceedings of the seventh annual ACM symposium on Parallel algorithms and architectures
Quantifying Locality Effect in Data Access Delay: Memory logP
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
A Parallel Computational Model for Heterogeneous Clusters
IEEE Transactions on Parallel and Distributed Systems
CCGRID '07 Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid
CellSs: making it easier to program the cell broadband engine processor
IBM Journal of Research and Development
Modeling advanced collective communication algorithms on cell-based systems
Proceedings of the 15th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
Modeling multigrain parallelism on heterogeneous multi-core processors: a case study of the cell BE
HiPEAC'08 Proceedings of the 3rd international conference on High performance embedded architectures and compilers
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Due to the heterogeneity and the multigrain parallelism of the heterogeneous multi-core computer, communication and memory access show hierarchical characteristics ignored by other models. In this paper, a new model named mPlogP, is presented on the basis of the PlogP model, in which communication and memory access is abstracted by considering these new characteristics of the heterogeneous multi-core computer. It uses memory access to model the behavior of computation, estimates the execution time of every part of applications and guides the optimization of effective parallel programs. Finally this proposed model is validated by experiments that it can precisely evaluate the execution of parallel applications under the heterogeneous multi-core computer.