Acknowledgement:  Microsoft NNI Team Hyper-parameter tuning (HPT) is an essential step in deep learning workflows, allowing teams to push a model’s quality higher by systematically evaluating many different sets of hyper-parameters (each called a “trial”) and picking the best outcome. HPT is appealing because it is easy to automate and requires little engineering or coding. […]

What is AdaptDL? Petuum is very excited to announce the launch of our newest open source offering, AdaptDL, a resource-adaptive deep learning (DL) training and scheduling framework. The goal of AdaptDL is to make distributed DL easy and efficient in dynamic-resource environments such as shared clusters and the cloud. During our benchmark studies when using AdaptDL with […]

Introducing AutoDist Petuum is excited to announce our latest Open Source project, AutoDist, a distributed deep learning training engine. It provides an easy to use interface to automatically distribute the training of a wide variety of deep learning models across many CPUs and GPUs at scale with very minimal code change.   Why use AutoDist? Are you searching for an intuitive library […]

As recently presented at the International Cement Seminar & Conference by Edward Sullivan, Senior Vice President and Chief Economist for the Portland Cement Association (PCA), the cement demand for 2020 looks bright. PCA regularly releases forecasts and guidance to cement manufacturers for their market intelligence.