Leonid Karlinsky, Joseph Shtok, et al.
CVPR 2019
In this paper, we present several algorithms for performing all-to-many personalized communication on distributed memory parallel machines. We assume that each processor 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 from both the view of static scheduling and runtime scheduling. © 1995 Academic Press, Inc.
Leonid Karlinsky, Joseph Shtok, et al.
CVPR 2019
Kellen Cheng, Anna Lisa Gentile, et al.
EMNLP 2024
Ben Fei, Jinbai Liu
IEEE Transactions on Neural Networks
Ira Pohl
Artificial Intelligence