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
MPI versus MPI+OpenMP on IBM SP for the NAS benchmarks
Proceedings of the 2000 ACM/IEEE conference on Supercomputing
International Journal of Parallel Programming
Fast Measurement of LogP Parameters for Message Passing Platforms
IPDPS '00 Proceedings of the 15 IPDPS 2000 Workshops on Parallel and Distributed Processing
Compile-Time Based Performance Prediction
LCPC '99 Proceedings of the 12th International Workshop on Languages and Compilers for Parallel Computing
A framework for performance modeling and prediction
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
Performance comparison of MPI and three openMP programming styles on shared memory multiprocessors
Proceedings of the fifteenth annual ACM symposium on Parallel algorithms and architectures
Performance Modeling of Communication and Computation in Hybrid MPI and OpenMP Applications
ICPADS '06 Proceedings of the 12th International Conference on Parallel and Distributed Systems - Volume 2
Automatic Hybrid MPI+OpenMP Code Generation with llc
Proceedings of the 16th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
Hybrid bulk synchronous parallelism library for clustered smp architectures
Proceedings of the fourth international workshop on High-level parallel programming and applications
| Hi-index | 0.01 |
Clusters of symmetric multiprocessors (SMPs) are the most currently used architecture for large scale applications and combining MPI and OpenMP models is regarded as a suitable programming model for such architectures. But writing efficient MPI+OpenMP programs requires expertise and performance analysis to determine the best number of processes and threads for the optimal execution for a given application on a given platform. To solve these problems, we propose a framework for the development of hybrid MPI+OpenMP programs. This paper provides the following contributions: (i) A compiler analyser that estimates the computing time of a sequential function. (ii) A code generator tool for generating hybrid code based on the compiler analyser and a simple analytical parallel performance prediction model to estimate the execution time of an hybrid program. (iii) An evaluation of the accuracy of the framework and its usability on several benchmarks.