Markus Hohnerbach – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2024-04-09T23:45:29Z http://www.open-lab.net/blog/feed/ Markus Hohnerbach <![CDATA[cuTENSOR 2.0: Applications and Performance]]> http://www.open-lab.net/blog/?p=77915 2024-04-09T23:45:28Z 2024-03-09T03:20:47Z While part 1 focused on the usage of the new NVIDIA cuTENSOR 2.0 CUDA math library, this post introduces a variety of usage modes beyond that, specifically...]]>

While part 1 focused on the usage of the new NVIDIA cuTENSOR 2.0 CUDA math library, this post introduces a variety of usage modes beyond that, specifically usage from Python and Julia. We also demonstrate the performance of cuTENSOR based on benchmarks in a number of application domains. This post explores applications and performance benchmarks for cuTENSOR 2.0. For more information…

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Markus Hohnerbach <![CDATA[cuTENSOR 2.0: A Comprehensive Guide for Accelerating Tensor Computations]]> http://www.open-lab.net/blog/?p=77913 2024-04-09T23:45:29Z 2024-03-09T03:20:45Z NVIDIA cuTENSOR is a CUDA math library that provides optimized implementations of tensor operations where tensors are dense, multi-dimensional arrays or array...]]>

NVIDIA cuTENSOR is a CUDA math library that provides optimized implementations of tensor operations where tensors are dense, multi-dimensional arrays or array slices. The release of cuTENSOR 2.0 represents a major update—in both functionality and performance—over its predecessor. This version reimagines its APIs to be more expressive, including advanced just-in-time compilation capabilities all…

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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 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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