Best Practices for Multi-GPU Data Analysis Using RAPIDS with Dask

As we move towards a more dense computing infrastructure, with more compute, more GPUs, accelerated networking, and so forth—multi-gpu training and analysis…

As we move towards a more dense computing infrastructure, with more compute, more GPUs, accelerated networking, and so forth—multi-gpu training and analysis grows in popularity. We need tools and also best practices as developers and practitioners move from CPU to GPU clusters. RAPIDS is a suite of open-source GPU-accelerated data science and AI libraries. These libraries can easily scale-out for…

Source

Source:: NVIDIA