Dask Demo Day - How RAPIDS users use Dask

Transcript

1. How do folks use Dask + RAPIDS? Dask Demo Day Oct 2023
2. 2 25% of the Fortune 100 use RAPIDS
3. 3 Growing community
4. 4 Common RAPIDS use cases ▸ Workloads ◦ Dask-cuDF + XGBoost risk assessment on >1TB datasets ◦ LLM Text preprocessing on >10TB datasets ◦ Apache Beam pipelines ◦ Graph neural networks ▸ Sectors ◦ Retail ◦ Financial services ◦ Cyber security ◦ Telecoms ◦ Automotive ▸ Market size ◦ Some users spending 6-7 figures per month on GPU Dask clusters ◦ Clusters with up to 100 GPU workers Where do we see people using RAPIDS? ▸ Platforms ◦ Google Cloud ◦ AWS ◦ Azure ◦ Oracle ◦ On Prem (often SLURM) ▸ Dask often paired with ◦ XGBoost ◦ Optuna ◦ Spark ◦ Apache Beam ◦ Numba ◦ PyTorch ◦ Tensorflow
5. 5 Model evaluation in recommender systems https://www.nvidia.com/en-us/on-demand/session/gtcspring21-s32017/
6. 6 Feature processing in recommender systems https://www.nvidia.com/en-us/on-demand/session/gtcspring21-s32017/
7. 7 Signal processing in autonomous vehicles https://www.nvidia.com/en-us/on-demand/session/gtcspring23-s51336/
8. 8 LLM Data Preprocessing (10s of TBs) https://developer.nvidia.com/blog/curating-trillion-token-datasets-introducing-nemo-data-curator/
9. 9 Apache Beam Pipelines https://www.youtube.com/watch?v=uGEQkws1Low
10. 10 Open Source Community ▸ NVIDIA targets Large Enterprises with RAPIDS. ▸ Large Enterprise users are less likely to open GitHub issues than academic or SME users. ▸ RAPIDS users typically work for companies with direct links to NVIDIA for support. ▸ Dask issues are often discussed in high-level projects like dask-cudf, nvtabular, NeMo, etc Maybe we could do better at communicating back to the Dask community… Why don’t we see RAPIDS discussed more in OSS Dask?