Extending Block-Cyclic Tensors for Multi-GPU with NVIDIA cuTENSORMg – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2025-03-18T20:27:07Z http://www.open-lab.net/blog/feed/ Markus Hohnerbach <![CDATA[Extending Block-Cyclic Tensors for Multi-GPU with NVIDIA cuTENSORMg]]> http://www.open-lab.net/blog/?p=44419 2023-06-12T21:05:12Z 2022-04-08T22:50:53Z Tensor contractions are at the core of many important workloads in machine learning, computational chemistry, and quantum computing. As scientists and engineers...]]> Tensor contractions are at the core of many important workloads in machine learning, computational chemistry, and quantum computing. As scientists and engineers...The cuTensor hero image with a floating grey block.

Tensor contractions are at the core of many important workloads in machine learning, computational chemistry, and quantum computing. As scientists and engineers pursue ever-growing problems, the underlying data gets larger in size and calculations take longer and longer. When a tensor contraction does not fit into a single GPU anymore, or if it takes too long on a single GPU��

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