Table Of Contents
This repository contains sample applications for NVIDIA software tool working with GCP platforms (ai platform, Dataproc, GKE, etc). For some demos the sample code will be part of this repo, and for some demos we would link to some great demos outside of this repo.
- Install Google Cloud SDK on your laptop/client workstation, so that
gcloudSDK cli interface could be run on the client - In addition, user could leverage Google Cloud shell
- Triton autoscaling example with TensorRT optimization in Google Kubernetes Engine
- BERT fine tuning, TensorRT optimization, Serve TensorRT engine through Triton in AI Platform Prediction
- Triton Inference Server application in Google Kubernetes Engine
- Triton GKE Marketplace application, Blog
- AlphaFold batch inference with Vertex AI Pipelines
- Triton in Vertex AI Prediction
- XGBoost with LocalCUDACluster Dask single node sample
- RAPIDS XGBoost hyperparameter optimization example
- XGBoost ensemble inference with Triton
- RAPIDS/Spark on GCP Dataproc
- Churn example with Spark RAPIDS on GCP Dataproc
- TensorRT intergration with Dataflow
- TensorRT Bert Q&A inference in GCP Dataflow
- BigQuery analytics with Dask on GPU
- Building a Computer Vision Service Using NVIDIA NGC and Triton in Google Cloud
- NVIDIA Merlin recommender system on GCP Vertex AI
- AutoML Videl Edge on NVIDIA GPU
See the following resources to learn more about NVIDIA NGC and GPU resources in Google Cloud Platform
Documentation
- GPU in Google Cloud Platform
- Optimize GPU Performance in Google Cloud Platform
- Getting started with NGC on Google Cloud Platform
- DL Frameworks GPU Performance Optimization Recommendations
- Multi-Instance GPU User Guide for A100 GPU
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See LICENSE.
- Dong Meng (github: mengdong)
- Rajan Arora (github: roarjn)
- Ethem Can (github: ethem-kinginthenorth)
- Arun Raman (github: arunraman)