As the vast number-crunching enabled by artificial intelligence (AI) becomes a critical part of most organizations’ business models, finding the right tools, technologies and techniques to do the job effectively becomes ever more vital. To demonstrate how selecting the right components can maximize the effectiveness of AI tasks, Dell has benchmarked various Dell Precision Data Science Workstation configurations against both deep learning and machine learning workflows.

Dell’s analysis clearly demonstrates the substantial benefits of NVIDIA RTX GPU acceleration and includes all original data, so testing and validation of the findings is possible by third parties. One machine learning model training benchmark reveals that running on a CPU takes 6.4x longer than on a GPU configuration. While another deep learning benchmark shows up to 4.74x in speedup due to multi-GPU acceleration. The second half of this paper uses these findings to provide a simple best practice guide for selecting the optimum components for any workflow.

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