no code implementations • 7 Nov 2023 • Aaron Archer, Matthew Fahrbach, Kuikui Liu, Prakash Prabhu
We optimize pipeline parallelism for deep neural network (DNN) inference by partitioning model graphs into $k$ stages and minimizing the running time of the bottleneck stage, including communication.
no code implementations • 15 Apr 2020 • Nima Anari, Kuikui Liu, Shayan Oveis Gharan, Cynthia Vinzant
For a matroid of rank $k$ on a ground set of $n$ elements, or more generally distributions associated with log-concave polynomials of homogeneous degree $k$ on $n$ variables, we show that the down-up random walk, started from an arbitrary point in the support, mixes in time $O(k\log k)$.
Data Structures and Algorithms Discrete Mathematics Probability
