Using MPI - portable parallel programming with the message-parsing interface

By William D. Gropp, E. Lusk, Anthony Skjellum. 1994

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Adam Gaier
2. Roland Martin
3. Yuri Alexeev
4. Dimitri Komatitsch
5. Michael P. Mazanetz
6. Osamu Ichihara
7. David R Ha
8. André Rigland Brodtkorb

Citations in the corpus

• Weight Agnostic Neural Networks (2019, methodology): “rks A.1 Code Release We release a general purpose tool, not only to facilitate reproduction, but also for further research in this direction. Our NumPy [119] implementation of NEAT [110] supports MPI [33] and OpenAI Gym [11] environments. All code used to run these experiments, in addition to the be”
• Progress in the theory and interpretation of XANES (2005, methodology): “Parallelization has also been implemented in FEFF8 with the message-passing-interface (MPI) protocol [24].”
• A Survey on Distributed Machine Learning (2019, methodology): “, BLAS [89] or MPI [62]) have been successfully adopted and integrated into systems by the machine learning community.”
• X10: an object-oriented approach to non-uniform cluster computing (2005, methodology): “For MPI programs, a barrier is used to coordinate all members of a process group in a communicator [ 51 ].”