Interprocessor Communication with Limited Memory
IEEE Transactions on Parallel and Distributed Systems
Proceedings of the 22nd annual international conference on Supercomputing
Fine-Grained Data Distribution Operations for Particle Codes
Proceedings of the 16th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
A Memory-Efficient Data Redistribution Algorithm
Proceedings of the 16th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
Madre: the Memory-Aware Data Redistribution Engine
International Journal of High Performance Computing Applications
An in-place algorithm for irregular all-to-all communication with limited memory
EuroMPI'10 Proceedings of the 17th European MPI users' group meeting conference on Recent advances in the message passing interface
Journal of Computational Physics
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Monte Carlo neutron transport codes are a growing subject of research in nuclear reactor analysis. For robust reactor analysis, large scale neutron transport simulations require computation of reaction rates for tens of billions of particles involving several hundred isotopes. When employing physical-space domain decomposition, minimizing memory consumption while safely and efficiently exchanging massive amounts of data is a significant challenge. To address this problem, we implement and test several 芒聙聹memory-aware芒聙聺, in-place, sparse, all-to-all MPI communication implementations. The algorithms are developed and tested within the open source MADRE (Memory-Aware Data Redistribution) project, which gives application programmers a simple API and set of tools and algorithms for carrying out memory-transparent in-place communication. We explore memory and communication efficiency tradeoffs for a range of in-place algorithms using a simple Monte Carlo communication kernel intended to mimic the behavior of our full Monte Carlo neutronics code.