Catalina-2 intelligent storage devices now natively support containers, enabling applications to run with near-data processing.
Analytic applications in a variety of edge computing and IoT deployments are highly space-constrained, and cannot support traditional computing platforms,” said Vladimir Alves, Chief Technology Officer at NGD Systems. “By utilizing In-Situ Processing and new form factors such as EDSFF, these applications now have a powerful, high-density, low power computing solution. Our support for Docker extends these capabilities by allowing containerized applications to execute seamlessly within NGD Storage Devices.
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We have all seen demonstrations of the capabilities of Artificial Intelligence (AI)-based imaging applications, from facial recognition to computer vision assisted application platforms. However, scaling these imaging implementations to Petabyte-scale for real-time datasets is problematic because:
Utilizing brute-force methods on modern imaging databases, which can be in the petabyte-size range, is often both incredibly difficult and enormously expensive. This has forced organizations with extremely large image databases to look for new approaches to image similarity search and more generally to the problem of data storage and analysis.
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