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Wallaroo.AI and Ampere Computing Collaborate to Bring Energy-Efficient, Low-Cost Machine Learning Inferencing to the Cloud

Wallaroo.AI and Ampere Computing Collaborate to Bring Energy-Efficient, Low-Cost Machine Learning Inferencing to the Cloud

Wallaroo.AI, the leader iWallaroo.AI n scaling production machine learning (ML) from the cloud to the edge announced a strategic collaboration with Ampere Computing to create optimized hardware/software solutions that provide reduced energy consumption, greater efficiency, and lower cost per inference for cloud artificial intelligence (AI).

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“all of which is critical to meeting the huge demand for AI computing resources today also while addressing the sustainability impact of the explosion in AI.”

Ampere processors are inherently more energy efficient than traditional AI accelerators. Now, with an optimized low-code/no-code ML software solution and customized hardware, putting AI into production in the cloud has never been easier or more cost-effective (even at cost-per-inference measure) or used less energy.

“This Wallaroo.AI/Ampere solution allows enterprises to deploy easily, improve performance, increase energy efficiency, and balance their ML workloads across available compute resources much more effectively,” said Vid Jain, chief executive officer of Wallaroo.AI, “all of which is critical to meeting the huge demand for AI computing resources today also while addressing the sustainability impact of the explosion in AI.”

“Through this collaboration, Ampere and Wallaroo.AI are combining Cloud Native hardware and optimized software to make ML production within the cloud much easier and more energy-efficient,” said Jeff Wittich, Chief Product Officer at Ampere. “That means more enterprises will be able to turn AI initiatives into business value more quickly.”

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Breakthrough Cloud AI Performance

One of the key advantages of the collaboration is the integration of Ampere’s built-in AI acceleration technology and Wallaroo.AI’s highly-efficient Inference Server, part of the Wallaroo Enterprise Edition platform for production ML.

Benchmarks have shown as much as a 6x improvement over containerized x86 solutions on certain models like the open source ResNet-50 model. Tests were run using an optimized version of the Wallaroo Enterprise Edition on Dpsv5-series Azure virtual machines using Arm64 Azure virtual machines using Ampere Altra 64-bit processors; however, the optimized solution will also be available for other cloud platforms.

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[To share your insights with us, please write to sghosh@martechseries.com]

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