GPUs excel at data-parallel processing, due to their high bandwidth on-board memory and specialized hardware architecture. This has been extensively researched in prior work. However, GPUs' Achilles heel has long been the data rate at which they can access large data volumes. In this seminar, I will show that the modern CPU+GPU architectures such as NVIDIA Grace-Blackwell overcome this hurdle. Grace-Blackwell, with its NVLink C2C interconnect and hardware decompress engine, delivers data to the GPUs at very high input rates. I will introduce a prototype GPU query engine built by NVIDIA. This engine showcases the benefits of modern CPU+GPU architectures for relational query processing. Finally, I will discuss using NVLink to perform index lookups on large data, thereby reducing the data transfer volume. Overall, modern CPU+GPU architectures are highly relevant for GPU-accelerated data analytics.