109 citations · 616 across the 40 of their papers we have counts for
4 papers · 1 filter
Generating Configurable Hardware from Parallel Patterns
Raghu Prabhakar, David Koeplinger, Kevin Brown +4
In recent years the computing landscape has seen an in- creasing shift towards specialized accelerators. Field pro- grammable gate arrays (FPGAs) are particularly promising as they…
Rapidly Mixing Gibbs Sampling for a Class of Factor Graphs Using Hierarchy Width
Christopher De Sa, Ce Zhang, Kunle Olukotun +1
Gibbs sampling on factor graphs is a widely used inference technique, which often produces good empirical results. Theoretical guarantees for its performance are weak: even for tre…
Taming the Wild: A Unified Analysis of Hogwild!-Style Algorithms
Christopher De Sa, Ce Zhang, Kunle Olukotun +1
Stochastic gradient descent (SGD) is a ubiquitous algorithm for a variety of machine learning problems. Researchers and industry have developed several techniques to optimize SGD's…
EmptyHeaded: A Relational Engine for Graph Processing
Christopher R. Aberger, Susan Tu, Kunle Olukotun +1
There are two types of high-performance graph processing engines: low- and high-level engines. Low-level engines (Galois, PowerGraph, Snap) provide optimized data structures and co…