Capture and analyze large amounts of data in tactical edge and distributed edge environments, instantly and in the field, with the power of GPU computing
A New Solution for Edge Data Capture and Processing
Capturing and analyzing large amounts of data in edge environments has been a big challenge due to the size of the data and limited compute resources. This is particularly true in edge environments with limited or no networking infrastructure. Organizations would either have to send data to a data center for processing and analysis or their edge environments would be limited by minimal compute resources and storage capacity.
Now there is a solution that brings GPU processing power to these edge environments.
The solution combines Gryf – a suitcase-sized AI supercomputer co-designed by Sourcecode and GigaIO – with the Hammerspace Global Data Platform so that large amounts of data generated at the edge can now be captured and analyzed immediately in the field.
This solution is highly relevant for use cases such as capturing large map sets and other types of geospatial data in tactical edge environments for satellite ground stations and for natural disaster response, and it is an effective way to transport large amounts of data quickly.
Gryf Brings GPU Processing Power to Edge Environments
Gryf is a portable supercomputer in a ruggedized suitcase form factor for rapid AI processing of time-sensitive data in the field, also referred to as a mobile fly-away kit. It is a high-performance modular compute platform that is lightweight and durable, and fits in an overhead bin.
Hammerspace Enables High Speed Processing and Orchestration of Data Across Distributed Edge Environments
Hammerspace can run on a single Gryf appliance alongside other software packages like Cyber, geospatial, Kubernetes containerized applications, and other AI analytic packages.
Hammerspace’s standards-based parallel file system architecture combines extreme parallel processing speed with the simplicity of NFS, making it ideal for ingesting and processing the large amounts of unstructured data generated by sensors, drones, satellites, cameras and other devices at the edge.
The full benefit of Hammerspace is unlocked when multiple Gryf appliances are deployed across a distributed edge environment so that Hammerspace can join multiple locations together into a single Global Namespace.
Hammerspace Data Orchestration services enable full utilization of all available GPU resources to accelerate edge processing. This capability is extremely beneficial for AI at the edge, where limited hardware, bandwidth and connectivity constraints are common challenges.
And Data Orchestration also simplifies the movement and migration of data when Gryf appliances are transported back to data centers for additional data analysis and long-term protection.