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Fujitsu Primergy M7, sustainable digital transformation

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Fujitsu Primergy M7, sustainable digital transformation

Fujitsu Primergy M7 servers: Equipped with the right computing capacity to make sustainable digital transformation programs faster and more cost-effective.

Thanks to best levels of performance and energy efficiency in their class, Fujitsu Primergy M7 systems, equipped with the fourth generation Intel Xeon Scalable Processor Platform technology. offer the simplicity and cost profile needed for operational backbones.

Hardware and test environment

As a demonstration of their flexibility, Fujitsu will immediately adopt the M7 servers in its AI Test Drive facility, part of the Fujitsu DX Innovation Platform. Everything is made accessible in Italy by FINIX Technology Solutions, which exclusively markets the solutions from the Fujitsu offer. The AI ā€‹ā€‹Test Drive helps professionals test business cases for AI applications, thereby overcoming the main hurdle data scientists often face. That is, finding the hardware and environment needed to run tests, before tackling onerous investments.

fujitsu primer

Faster sustainable digital transformation

The test environment, which is free to use, provides a full package of computing capabilities, including the top-of-the-line Fujitsu Primergy RX8770 M7 8-socket rack server. The package includes network connectivity, optimization using open source tools and support, everything you need to evaluate the feasibility of the business case of an AI-based project.

Deep learning activities

The new Fujitsu Primergy M7 server portfolio offers a choice of Intel CPUs and the most sophisticated and specialized approach to GPUs (Graphics Processing Units) used in AI. M7 servers pave the way for CPU-based AI tasks, thanks to innovations like Intel’s distribution of the OpenVINO Toolkit. A solution that simplifies the deployment of inference associated with deep learning for hundreds of pre-trained models. As a result, CPUs and the software libraries that rely on them have evolved, becoming significantly more adept at deep learning tasks. CPU-based systems are also simpler and more robust. Like in edge environments, where low power requirements are best suited.

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