High Performance Computing (HPC) with Flywheel

Flywheel now provides additional support for customers’ existing infrastructure and workflows with two significant advances.   

HPC with Singularity and Slurm

Flywheel has introduced support for High Performance Computing environments running singularity and Slurm. This integration enables users to save on computing costs and allows them to take advantage of significant investments made in existing computing resources. Flywheel Gears may be run on HPC clusters regardless of whether the Flywheel system is deployed on premises or in the cloud.

Rsync-like Data Access

CLI Sync provides users with an efficient method of syncing their Flywheel data with local file systems. This improved data portability allows customers to leverage pipelines and hardware not yet integrated with Flywheel. The rsync-like functionality ensures that only changes to data are migrated to local systems, thus saving time and cost.


Flywheel Introduces New Advanced Search

Flywheel augments its fast, powerful search tool with the introduction of Advanced Search, providing users the ability to construct complex queries and quickly pinpoint the data they need. When this feature is introduced, find Advanced Search by hitting ‘Enter’ in the Search Bar and clicking  ‘Advanced Search’.

Visual Query Builder

Advanced Search features a visual query builder, providing even the least technical users with the ability to quickly and easily construct highly specific queries.  Search queries may be saved for sharing and reuse.

Powerful SQL-Like Query Language

Users that are more familiar with SQL can manually construct queries using Flywheel’s simplified query language: FlyQL.  FlyQL enables access to all metadata, including DICOM tags and custom metadata.

Search Image Annotations and ROIs

With more and more customers looking to Flywheel to manage large, diverse data sets for Clinical Trials and Machine Learning projects, the need for improved data management tools has come to the forefront. With advanced search, users will have the ability to quickly and easily locate data across multiple projects matching any number of criteria.     AI Developers can search for annotated images, including by regions of interest (ROIs), and create machine learning training sets with ease. Researchers can quickly locate subjects based on custom metadata to create collections or run batch analysis directly from search results.