From c126ecf5f698ca5cd6a8ca5396b517ccd0acd382 Mon Sep 17 00:00:00 2001 From: John Calderon Date: Fri, 31 Mar 2023 12:47:02 -0400 Subject: [PATCH] changed readme --- README.md | 45 +++++++++++++++++++++++++-------------------- 1 file changed, 25 insertions(+), 20 deletions(-) diff --git a/README.md b/README.md index 38dd8d0..4d6f1fd 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,4 @@ -# Habitat +# DeepView.Predict [![License](https://img.shields.io/badge/license-Apache--2.0-green?style=flat)](https://github.com/CentML/habitat/blob/main/LICENSE) [![Maintainability](https://api.codeclimate.com/v1/badges/fbb68badd0c0599f1843/maintainability)](https://codeclimate.com/github/CentML/DeepView.Predict/maintainability) @@ -17,11 +17,11 @@ A Runtime-Based Computational Performance Predictor for Deep Neural Network Trai - [Research paper](#paper) - [Contributing](#contributing) -Habitat is a tool that predicts a deep neural network's training iteration execution time on a given GPU. It currently supports PyTorch. To learn more about how Habitat works, please see our [research paper](https://arxiv.org/abs/2102.00527). +DeepView.Predict is a tool that predicts a deep neural network's training iteration execution time on a given GPU. It currently supports PyTorch. To learn more about how DeepView.Predict works, please see our [research paper](https://arxiv.org/abs/2102.00527).

Installation

-To run Habitat, you need: +To run DeepView.Predict, you need: - [Python 3.6+](https://www.python.org/) - [Pytorch 1.1.0+](https://pytorch.org/) - A system equiped with an Nvidia GPU with properly configured CUDA @@ -37,12 +37,17 @@ Currently, we have predictors for the following Nvidia GPUs: | 2080Ti | Turing | 11 GB | GDDR6 | 68 | | T4 | Turing | 16 GB | GDDR6 | 40 | | 3090 | Ampere | 24 GB | GDDR6X | 82 | +| A100 | Ampere | 40 GB | HBM2 | 108 | +| A40 | Ampere | 48 GB | GDDR6 | 84 | +| A4000 | Ampere | 16 GB | GDDR6 | 48 | +| 4000 | Turing | 8 GB | GDDR6 | 36 | +

Building locally

### 1. Install CUPTI -CUPTI is a profiling interface required by Habitat. Select your version of CUDA [here](https://developer.nvidia.com/cuda-toolkit-archive) and follow the instructions to add NVIDIA's repository. Then, install CUPTI with: +CUPTI is a profiling interface required by DeepView.Predict. Select your version of CUDA [here](https://developer.nvidia.com/cuda-toolkit-archive) and follow the instructions to add NVIDIA's repository. Then, install CUPTI with: ```bash sudo apt-get install cuda-cupti-xx-x ``` @@ -54,7 +59,7 @@ Alternatively, if you do not have root access on your machine, you can use `cond ``` After installing CUPTI, add `$CONDA_HOME/extras/CUPTI/lib64/` to `LD_LIBRARY_PATH` to ensure the library is linked. -### 2. Install Habitat +### 2. Install DeepView.Predict You can install via pip if you have the following versions of CUDA and Python @@ -77,12 +82,12 @@ For example, if you are using CUDA 10.2 and Python 3.7): pip install http://centml-releases.s3-website.us-east-2.amazonaws.com/habitat/wheels/habitat_predict-1.0.0-20221123+cu102-py37-none-any.whl ``` -If you do not find matching version of CUDA and Python above, you need to build Habitat from source with the following instructions +If you do not find matching version of CUDA and Python above, you need to build DeepView.Predict from source with the following instructions ### Installing from source 1. Install CMake 3.17+. - - Note that CMake 3.24.0 and 3.24.1 has a bug that breaks Habitat as it is not able to find the CUPTI directory and you should not use those versions + - Note that CMake 3.24.0 and 3.24.1 has a bug that breaks DeepView.Predict as it is not able to find the CUPTI directory and you should not use those versions - [https://gitlab.kitware.com/cmake/cmake/-/merge_requests/7608/diffs](https://gitlab.kitware.com/cmake/cmake/-/merge_requests/7608/diffs) - Run the following commands to download and install a precompiled version of CMake 3.24.2 @@ -101,20 +106,20 @@ If you do not find matching version of CUDA and Python above, you need to build ``` 2. Install [Git Large File Storage](https://git-lfs.github.com/) -3. Clone the Habitat package +3. Clone the DeepView.Predict package ```bash - git clone https://github.com/centml/habitat + git clone https://github.com/CentML/DeepView.Predict ``` -4. Get the pre-trained models used by Habitat +4. Get the pre-trained models used by DeepView.Predict ```bash git submodule init && git submodule update git lfs pull ``` -5. Finally build habitat with the following command +5. Finally build DeepView.Predict with the following command ```bash ./analyzer/install-dev.sh @@ -122,23 +127,23 @@ If you do not find matching version of CUDA and Python above, you need to build

Building with Docker

-Habitat has been tested to work on the latest version of [NVIDIA NGC PyTorch containers](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch). +DeepView.Predict has been tested to work on the latest version of [NVIDIA NGC PyTorch containers](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch). -1. To build Habitat with Docker, first run the NGC container where +1. To build DeepView.Predict with Docker, first run the NGC container where ```bash docker run --gpus all -it --rm nvcr.io/nvidia/pytorch:XX.XX-py3 ``` -2. Inside the container, clone the repository then build and install the Habitat Python package: +2. Inside the container, clone the repository then build and install DeepView.Predict Python package: ```bash -git clone --recursive https://github.com/centml/habitat +git clone --recursive https://github.com/CentML/DeepView.Predict ./habitat/analyzer/install-dev.sh ``` -**Note:** Habitat needs access to your GPU's performance counters, which requires special permissions if you are running with a recent driver (418.43 or later). If you encounter a `CUPTI_ERROR_INSUFFICIENT_PRIVILEGES` error when running Habitat, please follow the instructions [here](https://developer.nvidia.com/ERR_NVGPUCTRPERM) and in [issue #5](https://github.com/geoffxy/habitat/issues/5). +**Note:** DeepView.Predict needs access to your GPU's performance counters, which requires special permissions if you are running with a recent driver (418.43 or later). If you encounter a `CUPTI_ERROR_INSUFFICIENT_PRIVILEGES` error when running DeepView.Predict, please follow the instructions [here](https://developer.nvidia.com/ERR_NVGPUCTRPERM) and in [issue #5](https://github.com/geoffxy/habitat/issues/5).

Usage example

-You can verify your Habitat installation by running the simple usage example: +You can verify your DeepView.Predict installation by running the simple usage example: ```python # example.py import habitat @@ -166,7 +171,7 @@ print("Predicted time on V100:", pred.run_time_ms) python3 example.py ``` -See [experiments/run_experiment.py](https://github.com/CentML/habitat/tree/main/experiments) for other examples of Habitat usage. +See [experiments/run_experiment.py](https://github.com/CentML/DeepView.Predict/tree/main/experiments) for other examples of Habitat usage.

Release History

@@ -195,11 +200,11 @@ more information.

Research Paper

-Habitat began as a research project in the [EcoSystem Group](https://www.cs.toronto.edu/ecosystem) at the [University of Toronto](https://cs.toronto.edu). The accompanying research paper appeared in the proceedings of [USENIX +DeepView.Profile began as a research project in the [EcoSystem Group](https://www.cs.toronto.edu/ecosystem) at the [University of Toronto](https://cs.toronto.edu). The accompanying research paper appeared in the proceedings of [USENIX ATC'21](https://www.usenix.org/conference/atc21/presentation/yu). If you are interested, you can read a preprint of the paper [here](https://arxiv.org/abs/2102.00527). -If you use Habitat in your research, please consider citing our paper: +If you use DeepView.Profile in your research, please consider citing our paper: ```bibtex @inproceedings{habitat-yu21,