Deep Learning Training with BigDL and Drizzle (Ding Ding & Shivaram Venkataraman)

Ding Ding, a software engineer on Intel's big data technology team, and Shivaram Venkataraman, a post-doctoral researcher at Microsoft Research, discuss how the BigDL framework scales deep learning for large data sets using Apache Spark. However there is significant scheduling overhead from Spark when running BigDL at large scale. In this talk we propose a new parameter manager implementation that along with coarse-grained scheduling can provide significant speedups for deep learning models like Inception, VGG etc. Aggregation functions like reduce or treeReduce that are used for parameter aggregation in Apache Spark (and the original MapReduce) are slow as the centralized scheduling and driver network bandwidth become a bottleneck especially in large clusters.
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