179 citations · 195 across the 5 of their papers we have counts for
5 papers
Glow: Graph Lowering Compiler Techniques for Neural Networks
Nadav Rotem, Jordan Fix, Saleem Abdulrasool +15
This paper presents the design of Glow, a machine learning compiler for heterogeneous hardware. It is a pragmatic approach to compilation that enables the generation of highly opti…
Near-Constant-Time Distributed Algorithms on a Congested Clique
James W. Hegeman, Sriram V. Pemmaraju, Vivek B. Sardeshmukh
This paper presents constant-time and near-constant-time distributed algorithms for a variety of problems in the congested clique model. We show how to compute a 3-ruling set in ex…
Lessons from the Congested Clique Applied to MapReduce
James W. Hegeman, Sriram V. Pemmaraju
The main results of this paper are (I) a simulation algorithm which, under quite general constraints, transforms algorithms running on the Congested Clique into algorithms running…
A Super-Fast Distributed Algorithm for Bipartite Metric Facility Location
James Hegeman, Sriram V. Pemmaraju
The \textit{facility location} problem consists of a set of \textit{facilities} , a set of \textit{clients} , an \textit{opening cost} associated wi…
Super-Fast Distributed Algorithms for Metric Facility Location
Andrew Berns, James Hegeman, Sriram V. Pemmaraju
This paper presents a distributed O(1)-approximation algorithm, with expected- running time, in the model for the metric facility location probl…