Nervana Cloud 1.5.0 contains enormous under-the-hood changes and improvements. We’ve revamped and updated a lot of the core underlying code, separated the various application components into their own microservices, re-written our job launcher, added support for a new container orchestration service, squashed more than 75 bugs, and greatly expanded our testing coverage. The biggest changes visible to the end user are the aeon dataloader and auxiliary file volume support.
Aeon dataloader – The aeon dataloader enables fast and flexible access to training data sets that are too large to load directly into memory. Data is first loaded in chunks called “macrobatches” that are then split further into minibatches to feed the model. An easy interface enables you to configure the dataloader for custom datasets and to load data from disk with minimal latency. A manifest file is used to indicate your local input and target paths. On the backend we’ve built an entirely new data service to handle fetching, caching, and serving requests for dataset batches. See the Aeon User Guide for more information.
Auxiliary file volume support – We’ve also introduced support for arbitrary file volumes to handle non-aeon formatted data such as older datasets, vocabulary files, and output data. The volumes are mounted read/write during model training and inference jobs. You can append new files to existing volumes or download their contents. See Attaching Data for details on how to use this feature.
This release of Nervana Cloud includes a number of additional features and fixes: