SBIR-STTR Award

The overall research objective is to demonstrate advanced heterogenous computing solutions using widely available and relatively inexpensive commercial off the shelf technology. This solution will minimize SWaPC requirements for AI/ML applications, affording access to AI/ML solutions on the edge or accelerated performance of existing infrastructure. This solution will demonstrate the benefits of a heterogeneous compute environment to image processing and data analysis like packet capture (PCAP).heterogeneous high-performance compute,artificial intelligence,machine learning,Software,Hardware,edge processing

BlackLunx is proposing an innovating "edge-to-cloud" algorithmic processing capability in conjuction with AFLCMC/HNA support. BlackLynx will work with the customer and end users to define, develop, and produce a flyable edge analytics card using the OpenVPX data bus standard, as well as an on premises COTS-based analytics solution to close the gap from data to decision. The on premises solution will also include a network link, when available and operationally relevant, to a commerical cloud provider to be defined by the government customer. This solution will provide warfighters and senior decision makers with an analytics platform for forward-deployed units and/or in contested environments where reachback to hybrid computing solutions is denied. When the operating environment is uncontested, BlackLynx will pass data to a commercial cloud provider for long-term storage and more robust analytics processing.