AI Examples

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The UFIT Research Computing AI Support Team maintains a suite of examples for AI software stacks on UF Research Computing Github and on HiPerGator, located in /data/ai/examples. Users may copy these examples to their own space, add modifications, and follow the instructions to run these jobs on HiPerGator. Each example has a readme file with additional information in its directory.

Use https://support.rc.ufl.edu to submit ticket if you need help with the examples or have any AI questions.

Research Computing Github

We have some AI examples available on the UF Research Computing Github.

Catalog of available examples

Name Categories Location on HiPerGator Author Date added Description

Build Digital Twins using NVIDIA Omniverse and on HiPerGator Tutorial Simulation and Modeling /data/ai/examples/Omniverse Yunchao Yang June, 2024 This tutorial (slides) introduces a few key compoents of Omniverse and how to start using Omniverse on HiPerGator.
Modulus single-GPU and multi-GPU example PINN /data/ai/examples/pinn/modulus Yang Hong May, 2024 Modulus single-GPU Jupyter-notebook example is for using PINN to approximate the solution of a given PDE and boundary conditions. The multi-GPU example is for using GraphNN accelerates MD simulations to predict the force of each atom in the system.
Distributed Neural Network Training with Multiple GPUs Tutorial Multi-GPU /data/ai/examples/distributed-compute/MultiGPUTraining Yunchao Yang June, 2024 This example illstrates how to accelerate neural network training with Pytorch DistributedDataParallel on Multiple GPUs.
RAPIDS Data Science /data/ai/examples/rapids Dimitri Bourilkov April, 2024 Examples for accelerated data science with RAPIDS.
Rapids_singlecell Healthcare and Life Science /data/ai/examples/rapids_singlecell Huiwen Ju and Qian Zhao May, 2024 Rapids-singlecell offers enhanced single-cell data analysis as a near drop-in replacement predominantly for scanpy
Llama NLP /data/ai/examples/llms/llama Qian Zhao May, 2024 This tutorial demonstrates how to perform prompt engineering
NVIDIA Clara Parabricks Healthcare and Life Science /data/ai/examples/parabricks Huiwen Ju and Qian Zhao May, 2024 NVIDIA Clara Parabricks is a powerful genomics analysis software suite that leverages accelerated computing to process data efficiently.
NeMo Question Answering NLP /data/ai/examples/nlp/nemo_question_answeing Qian Zhao May, 2024 This tutorial shows how to perform question-answering with NVIDIA NeMo using BERT
TensorFlow+Keras Convolutional Neural Net Computer Vision /data/ai/examples/image/tensorflow-bootcamp Dimitri Bourilkov May, 2024 TensorFlow+Keras Convolutional Neural Net with NGC container
PyTorch Convolutional Neural Net Computer Vision /data/ai/examples/image/pytorch Dimitri Bourilkov July, 2021 PyTorch Convolutional Neural Net with NGC container
TensorFlow Convolutional Neural Net Computer Vision /data/ai/examples/image/tensorflow Dimitri Bourilkov July, 2021 PyTorch Convolutional Neural Net with NGC container
PyTorch Convolutional Neural Net Computer Vision /data/ai/examples/image/pytorch-bootcamp Dimitri Bourilkov April, 2024 PyTorch Convolutional Neural Net with NGC container
Object Detection Tutorial Computer Vision /data/ai/examples/image/4.Object_Detection_Tutorial Yunchao Yang Oct, 2022 This example illstrates how to generate a object detection on a video using pretrained models.
OpenCV Intro Tutorial Computer Vision /data/ai/examples/image/1.OpenCV_Intro_Tutorial Yunchao Yang Oct, 2022 This example illustrates the fundamentals of image processing techniques in opencv.
PyTorch Instance Segmentation Tutorial Computer Vision /data/ai/examples/image/5.PyTorch_Instance_Segmentation_Tutorial Yunchao Yang Oct, 2022 This example illstrates how to train an instance segementation model using mask r-cnn model
PyTorch Transfer Learning Tutorial Computer Vision /data/ai/examples/image/3.PyTorch_Transfer_Learning_Tutorial Yunchao Yang Oct, 2022 This example illstrates how to train a convolutional neural network for image classification using transfer learning.
TorchVision Intro Tutorial Computer Vision /data/ai/examples/image/2.TorchVision_Transforms_Tutorial Yunchao Yang Oct, 2022 This example illustrates the fundamentals of TorchVision in image transformation and augmentation
Building_GCN.py Graphs /data/ai/examples/graphs Dimitri Bourilkov June, 2024 Building Feed-Forward Graph Convolutional Networks (GCN) based on a paper by Thomas Kipf and Max Welling (https://arxiv.org/pdf/1609.02907.pdf). Imple
NetworkX and Numpy. mented using PyTorch
MONAI Medical Images Classification Tutorial Medical Image Processing /data/ai/examples/image/6.MONAI_Medical_Imaging_Tutorial Yunchao Yang Oct, 2022 This example illstrates how to train an medical image classification model using MONAI
AI News GPT NLP /data/ai/examples/nlp/ai_news_GPT Eric Stubbs March, 2023 See how trained from scratch GPT models can enable knowledge exploration or brainstorming. This example also shows how transfer learning, amount of data, and finetuning affect GPT models.
Example Multinode GPT Pretraining Mulit-GPU /data/ai/examples/distributed-compute/pytorch_distributed_exampleGPT Eric Stubbs July, 2021 Use the pytorch distributed launch utility to pretrain a GPT language model using multiple nodes.
Improved Megatron GPT Text Generation NLP /data/ai/examples/nlp/megatronGPT_text_generation/megatronGPT_text_generation Eric Stubbs August, 2022 Megatron code was updated to allow for bulk prompt completion and language generation using a 23 billion parameter Megatron GPT language model trained by UFIT Research Computing.
Language Model Inference Apps NLP /data/ai/examples/nlp/inference_apps Eric Stubbs May, 2022 Explore knowledge in Nvidia Megatron BERT and GPT models using notebooks by creating lists of the most likely predicted words.
MNLI Benchmark with UF Model NLP /data/ai/examples/nlp/multinli_benchmark Eric Stubbs August, 2022 Apply a 9 billion parameter Megatron BERT language model trained by UFIT Research Computing to an inference benchmark using improved code from Megatron. The model achieved a score of 87% after only 1 epoch of finetuning. State of the art score on NLI is 92%.