The next generation of Terra’s workflow execution capabilities will provide support for a wider range of tools and workflow languages.
Adam Nichols of the Terra Batch Workflows team takes us on a tour of the inner workings of the workflow execution system, highlighting recent improvements.
Why you should use workflows to automate your data processing, inspired by “Ten simple rules for large-scale data processing” (Fungtammasan 2022).
Discover recent improvements to Terra workspaces that protect your work from accidental changes and give you more flexibility and control over how your data tables are displayed.
A review of Terra features supporting documentation for transfer of knowledge and reproducibility, inspired by “Ten simple rules for large-scale data processing” (Fungtammasan 2022)
New Terra features give you greater control over data storage and computing resources by exposing the regional architecture of the Google Cloud Platform in key parts of Terra.
Starting the week of September 20th, each new Terra workspace will be associated with a dedicated Google project, which will allow us to improve the granularity of cost reporting in Terra.
Terra’s workflow management system now allows you to use a newer model of Intel CPUs than what the system normally uses by default to execute workflow tasks. You’ll be able to request “N2 instances” instead of “N1 instances”, which use 2nd Generation Intel® Xeon® Scalable Processors, codenamed “Cascade Lake”.
Terra has offered the ability to use GPUs in workflows for quite some time, yet many of you have told us that you also need to be able to run GPU-enabled computations interactively, so we’re really excited to roll out GPU support for Jupyter Notebooks.
We’ve added the ability to launch R Shiny apps from Terra’s built-in RStudio environment, opening up some really exciting possibilities for taking interactive data visualization in Terra to the next level.
Terra is developed by the Broad Institute of MIT and Harvard in collaboration with Microsoft and Verily.
