42 citations · 54 across the 7 of their papers we have counts for
3 papers · 1 filter
On the Computational Inefficiency of Large Batch Sizes for Stochastic Gradient Descent
Noah Golmant, Nikita Vemuri, Zhewei Yao +5
Increasing the mini-batch size for stochastic gradient descent offers significant opportunities to reduce wall-clock training time, but there are a variety of theoretical and syste…
Alchemist: An Apache Spark <=> MPI Interface
Alex Gittens, Kai Rothauge, Shusen Wang +6
The Apache Spark framework for distributed computation is popular in the data analytics community due to its ease of use, but its MapReduce-style programming model can incur signif…
Accelerating Large-Scale Data Analysis by Offloading to High-Performance Computing Libraries using Alchemist
Alex Gittens, Kai Rothauge, Shusen Wang +6
Apache Spark is a popular system aimed at the analysis of large data sets, but recent studies have shown that certain computations---in particular, many linear algebra computations…