Rangachari Anand, Kishan Mehrotra, et al.
IEEE Transactions on Neural Networks
In this paper, we present several algorithms for per forming all-to-many personalized communication on distributed memory parallel machines. Each proces sor sends a different message (of potentially different size) to a subset of all the processors involved in the collective communication. The algorithms are based on decomposing the communication matrix into a set of partial permutations. We study the effectiveness of our algorithms both from the view of static scheduling as well as runtime scheduling.
Rangachari Anand, Kishan Mehrotra, et al.
IEEE Transactions on Neural Networks
E.D. Kyriakis-Bitzaros, O.G. Koufopavlou, et al.
ICPP 1993
Soo-Mook Moon
ICPP 1993
Sanjay Ranka, Jhy-Chun Wang, et al.
Journal of Parallel and Distributed Computing