Difference between revisions of "AI Help"
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| − | [[Category: | + | [[Category:HPG-AI]] |
= New User's Guide = | = New User's Guide = | ||
| − | For new users on HiPerGator, please read [ | + | For new users on HiPerGator, please read [[Getting Started]] to get yourself familiar with HiPerGator system. |
| + | The [[Quick_Start_Guide|Quick Start Guide]] is a fast review. | ||
| − | For beginners, we have a series of pre-recorded [https://help.rc.ufl.edu/doc/Training training videos] available on a variety of topics. It is highly recommended that you watch these videos, such as Introduction to HiPerGator, SLURM job submission, and using [https://help.rc.ufl.edu/doc/Remote_Jupyter_Notebook Jupyter Hub] and [https://help.rc.ufl.edu/doc/Remote_Jupyter_Notebook Jupyter Notebooks], etc. | + | For beginners, we have a series of pre-recorded [https://help.rc.ufl.edu/doc/Training training videos] available on a variety of topics. It is highly recommended that you watch these videos, such as Introduction to HiPerGator, SLURM job submission, and using [https://help.rc.ufl.edu/doc/Remote_Jupyter_Notebook Jupyter Hub] and [https://help.rc.ufl.edu/doc/Remote_Jupyter_Notebook Jupyter Notebooks], etc. |
= AI Software = | = AI Software = | ||
| − | A comprehensive software stack for AI research is available on HiPerGator for both CPU and GPU accelerated applications. | + | A comprehensive software stack for AI research is available on HiPerGator for both CPU and GPU accelerated applications. The [[Nlp|NLP]] page has more info on software for NLP. |
== AI Frameworks == | == AI Frameworks == | ||
AI frameworks provide building blocks for designing and training machine learning and deep learning models. The following AI frameworks are available on HiPerGator. | AI frameworks provide building blocks for designing and training machine learning and deep learning models. The following AI frameworks are available on HiPerGator. | ||
| Line 15: | Line 16: | ||
=== Tensorflow/Keras === | === Tensorflow/Keras === | ||
[https://www.tensorflow.org/ TensorFlow] is an open-source AI framework/platform developed by the Google Brain team. [https://keras.io/ Keras] is an open-source neural network library which runs on top of TensorFlow. With TensorFlow 2.0, the Keras API has been integrated in TensorFlow's core library and serves as a high-level Python interface for TensorFlow. TensorFlow supports both GPU and CPUs, as well as multi-GPU and distributed training. APIs are available for Python, Java, Go and C++. See our [[TensorFlow|TensorFlow quickstart page]] for help getting started using TensorFlow on HiPerGator. | [https://www.tensorflow.org/ TensorFlow] is an open-source AI framework/platform developed by the Google Brain team. [https://keras.io/ Keras] is an open-source neural network library which runs on top of TensorFlow. With TensorFlow 2.0, the Keras API has been integrated in TensorFlow's core library and serves as a high-level Python interface for TensorFlow. TensorFlow supports both GPU and CPUs, as well as multi-GPU and distributed training. APIs are available for Python, Java, Go and C++. See our [[TensorFlow|TensorFlow quickstart page]] for help getting started using TensorFlow on HiPerGator. | ||
| + | |||
| + | === Tensorboard=== | ||
| + | [[Tensorboard]] is a visualization tool for monitoring neural network training. | ||
=== Sci-kit Learn === | === Sci-kit Learn === | ||
| − | Sci-kit learn is a Python library for machine learning and statistical modeling. It is available in '''[[Python]]''' | + | Sci-kit learn is a Python library for machine learning and statistical modeling. It is available in many of the '''[[Python]]''' modules on HiPerGator. |
=== MATLAB === | === MATLAB === | ||
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== NVIDIA AI Software == | == NVIDIA AI Software == | ||
Nvidia provides comprehensive, GPU-accelerated software libraries, toolkits, frameworks and packages for big-data and AI applications. Many of the libraries are included in the CUDA installation on HiPerGator, such as cuDNN. The following domain specific CUDA enabled tools are available on HiPerGator: | Nvidia provides comprehensive, GPU-accelerated software libraries, toolkits, frameworks and packages for big-data and AI applications. Many of the libraries are included in the CUDA installation on HiPerGator, such as cuDNN. The following domain specific CUDA enabled tools are available on HiPerGator: | ||
| + | |||
| + | === Megatron-LM === | ||
| + | [https://github.com/NVIDIA/Megatron-LM Megatron-LM] can train several architectures of language models, including an GPT, T5, and an improved BERT. Megatron also recently added a transformer-based image classification architecture. | ||
=== NeMo === | === NeMo === | ||
| − | [https://developer.nvidia.com/nvidia-nemo Nvidia NeMo] is an open-source | + | [https://developer.nvidia.com/nvidia-nemo Nvidia NeMo] is an open-source Python, GPU-accelerated toolkit for conversational AI, including speech recognition (ASR), natural language processing (NLP) and text to speech (TTS) applications. NeMo is available via a container in the apps folder. |
=== Clara Parabricks === | === Clara Parabricks === | ||
| − | [[Parabricks|Nvidia Clara Parabricks]] ([https://developer.nvidia.com/Clara-parabricks]) is a computation framework for genomics applications. It builds GPU accelerated libraries, pipelines and reference AI workflows for genomics research. | + | [[Parabricks|Nvidia Clara Parabricks]] ([https://developer.nvidia.com/Clara-parabricks]) is a computation framework for genomics applications. It builds GPU accelerated libraries, pipelines, and reference AI workflows for genomics research. We have a license for this software through 2021. |
| + | |||
| + | === Clara MONAI === | ||
| + | [[Monai|Nvidia Clara MONAI]] ([https://monai.io]) is the open-source foundation being created by Project MONAI. MONAI is a freely available, community-supported, PyTorch-based framework for deep learning in healthcare imaging. It provides domain-optimized foundational capabilities for developing healthcare imaging training workflows in a native PyTorch paradigm. | ||
| + | |||
| + | =AI Reference Datasets= | ||
| + | A variety of reference machine learning and AI datasets are located in <code>/data/ai</code>. Browse the [[AI Reference Datasets|catalog of all available AI reference datasets]] to learn more. | ||
Revision as of 00:34, 26 October 2021
New User's Guide
For new users on HiPerGator, please read Getting Started to get yourself familiar with HiPerGator system. The Quick Start Guide is a fast review.
For beginners, we have a series of pre-recorded training videos available on a variety of topics. It is highly recommended that you watch these videos, such as Introduction to HiPerGator, SLURM job submission, and using Jupyter Hub and Jupyter Notebooks, etc.
AI Software
A comprehensive software stack for AI research is available on HiPerGator for both CPU and GPU accelerated applications. The NLP page has more info on software for NLP.
AI Frameworks
AI frameworks provide building blocks for designing and training machine learning and deep learning models. The following AI frameworks are available on HiPerGator.
PyTorch
PyTorch is a deep learning framework developed by Facebook AI Research Lab and has interfaces for Python, Java, and C++, but is most commonly used with Python. It supports training on both GPU and CPUs, as well as distributed training and multi-GPU models. See our PyTorch quickstart page for help getting started using PyTorch on HiPerGator.
Tensorflow/Keras
TensorFlow is an open-source AI framework/platform developed by the Google Brain team. Keras is an open-source neural network library which runs on top of TensorFlow. With TensorFlow 2.0, the Keras API has been integrated in TensorFlow's core library and serves as a high-level Python interface for TensorFlow. TensorFlow supports both GPU and CPUs, as well as multi-GPU and distributed training. APIs are available for Python, Java, Go and C++. See our TensorFlow quickstart page for help getting started using TensorFlow on HiPerGator.
Tensorboard
Tensorboard is a visualization tool for monitoring neural network training.
Sci-kit Learn
Sci-kit learn is a Python library for machine learning and statistical modeling. It is available in many of the Python modules on HiPerGator.
MATLAB
Matlab provides convenient toolboxes for machine learning, deep learning, computer vision and automatic driving, which are supported on both CPUs and GPUs.
NVIDIA AI Software
Nvidia provides comprehensive, GPU-accelerated software libraries, toolkits, frameworks and packages for big-data and AI applications. Many of the libraries are included in the CUDA installation on HiPerGator, such as cuDNN. The following domain specific CUDA enabled tools are available on HiPerGator:
Megatron-LM
Megatron-LM can train several architectures of language models, including an GPT, T5, and an improved BERT. Megatron also recently added a transformer-based image classification architecture.
NeMo
Nvidia NeMo is an open-source Python, GPU-accelerated toolkit for conversational AI, including speech recognition (ASR), natural language processing (NLP) and text to speech (TTS) applications. NeMo is available via a container in the apps folder.
Clara Parabricks
Nvidia Clara Parabricks ([1]) is a computation framework for genomics applications. It builds GPU accelerated libraries, pipelines, and reference AI workflows for genomics research. We have a license for this software through 2021.
Clara MONAI
Nvidia Clara MONAI ([2]) is the open-source foundation being created by Project MONAI. MONAI is a freely available, community-supported, PyTorch-based framework for deep learning in healthcare imaging. It provides domain-optimized foundational capabilities for developing healthcare imaging training workflows in a native PyTorch paradigm.
AI Reference Datasets
A variety of reference machine learning and AI datasets are located in /data/ai. Browse the catalog of all available AI reference datasets to learn more.