100GB/s GPU log analytics at Graphistry: A case study and production lessons on tuning dask-cudf

Going from pandas or cudf to dask-cudf can unlock big and latency-sensitive analytics workloads… if done right. However, dask-cudf is quite new and multi-GPU computing faces NUMA hazards. This talk shares our experience with dask-cudf from two perspectives: A case study in tackling 100 GB/s for extracting an identity graph from big logs, and our top lessons in going to production.

Categories: Day 3