Adaptive Load Balancing for MPI Programs
ICCS '01 Proceedings of the International Conference on Computational Science-Part II
Development of mixed mode MPI / OpenMP applications
Scientific Programming
Hybrid parallel programming with MPI and unified parallel C
Proceedings of the 7th ACM international conference on Computing frontiers
Compact and efficient implementation of the MPI group operations
EuroMPI'10 Proceedings of the 17th European MPI users' group meeting conference on Recent advances in the message passing interface
PAMI: A Parallel Active Message Interface for the Blue Gene/Q Supercomputer
IPDPS '12 Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium
MPI-ACC: An Integrated and Extensible Approach to Data Movement in Accelerator-based Systems
HPCC '12 Proceedings of the 2012 IEEE 14th International Conference on High Performance Computing and Communication & 2012 IEEE 9th International Conference on Embedded Software and Systems
Proceedings of the 1st Workshop on Architectures and Systems for Big Data
Leveraging MPI's one-sided communication interface for shared-memory programming
EuroMPI'12 Proceedings of the 19th European conference on Recent Advances in the Message Passing Interface
Ownership passing: efficient distributed memory programming on multi-core systems
Proceedings of the 18th ACM SIGPLAN symposium on Principles and practice of parallel programming
NUMA-aware shared-memory collective communication for MPI
Proceedings of the 22nd international symposium on High-performance parallel and distributed computing
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The current MPI model defines a one-to-one relationship between MPI processes and MPI ranks. This model captures many use cases effectively, such as one MPI process per core and one MPI process per node. However, this semantic has limited interoperability between MPI and other programming models that use threads within a node. In this paper, we describe an extension to MPI that introduces communication endpoints as a means to relax the one-to-one relationship between processes and threads. Endpoints enable a greater degree interoperability between MPI and other programming models, and we illustrate their potential for additional performance and computation management benefits through the decoupling of ranks from processes.