A recent press release states, “GridGain Systems, provider of enterprise-grade in-memory computing solutions based on Apache® Ignite™, today announced the immediate availability of GridGain Professional Edition 2.7, a fully supported version of Apache Ignite 2.7. GridGain Professional Edition 2.7 introduces TensorFlow™ integration for enhanced training of deep learning (DL) models. GridGain Professional Edition 2.7 also provides enhanced usability, including expanded support for thin clients, as well as Transparent Data Encryption at rest to improve security. Together, the features make it easier to use the GridGain In-Memory Computing Platform for more use cases, such as for achieving the speed and scalability required for implementing real-time continuous learning for digital transformation and omnichannel customer experience initiatives.”

The release continues, “TensorFlow, a popular open source deep learning framework, is a software library for high performance numerical computation. Its flexible architecture allows for easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs) and devices. The GridGain integration with TensorFlow allows GridGain users to easily share data stored in GridGain with TensorFlow. Functioning as an in-memory data source for TensorFlow, GridGain allows users to leverage the TensorFlow deep learning framework for real-time deep learning model training without requiring a dedicated data store for TensorFlow. GridGain Professional Edition 2.7 also includes new preprocessing APIs and additional machine learning (ML) algorithms. These algorithms make it easier for organizations to apply the power of GridGain in-memory computing capabilities to more ML use cases such as credit card fraud detection, mortgage approvals, or ecommerce product recommendations.”

Read more at Globe Newswire.

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