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AI-Hypercomputer/gpu-recipes: Recipes for reproducing training and serving benchmarks for large machine learning models using GPUs on Google Cloud.
Reproducible benchmark recipes for GPUs
Welcome to the reproducible benchmark recipes repository for GPUs! This repository contains recipes for reproducing training and serving benchmarks for large machine learning models using GPUs on Google Cloud.
- Identify your requirements: Determine the model, GPU type, workload, framework, and orchestrator you are interested in.
- Select a recipe: Based on your requirements use the Benchmark support matrix to find a recipe that meets your needs.
- Follow the recipe: each recipe will provide you with procedures to complete the following tasks:
- Prepare your environment
- Run the benchmark
- Analyze the benchmarks results. This includes not just the results but detailed logs for further analysis
Benchmarks support matrix Training benchmarks A3 Mega Training benchmarks A3 Ultra Inference benchmarks A3 Mega Inference benchmarks A3 Ultra Models GPU Machine Type Framework Workload Type Orchestrator Link to the recipe Llama-3.1-70B A3 Mega (NVIDIA H100) NeMo Pre-training using Google Cloud Storage buckets for checkpoints GKE Link Models GPU Machine Type Framework Workload Type Orchestrator Link to the recipe Llama-3.1-70B A3 Mega (NVIDIA H100) NeMo Pre-training using the Google Cloud Resiliency library GKE Link Llama-3.1-405B A3 Ultra (NVIDIA H200) NeMo Pre-training using the Google Cloud Resiliency library GKE Link Mixtral-8x7B A3 Ultra (NVIDIA H200) NeMo Pre-training using the Google Cloud Resiliency library GKE Link
- training/: Contains recipes to reproduce training benchmarks with GPUs.
- inference/: Contains recipes to reproduce inference benchmarks with GPUs.
- src/: Contains shared dependencies required to run benchmarks, such as Docker and Helm charts.
- docs/: Contains supporting documentation for the recipes, such as explanation of benchmark methodologies or configurations.
If you have any questions or if you found any problems with this repository, please report through GitHub issues.
This is not an officially supported Google product. The code in this repository is for demonstrative purposes only.
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