MICRO22 Sparseloop Artifact

This repository provides the evaluation setups for MICRO22 artifact evaluation for the paper Sparseloop: An Analytical Modeling Approach to Sparse Tensor Accelerators. We provide a docker environment and a jupyter notebook for the artifect evlauation. Please contact timeloop-accelergy@mit.edu if there are any questions.

System requirement

Please install docker app

Perform artifact evaluation

Recursively clone repo

git clone --recurse-submodules git@github.com:Accelergy-Project/micro22-sparseloop-artifact.git
cd <cloned repo>
ls docker/

You should see the subdirectories in docker/ populated with actual source code instead of submodule pointers.

Step 0: Prepare your `docker-compose.yaml`

Create a docker compose file by making a copy of the docker compose tempalte file cp docker-compose.yaml.template docker-compose.yaml
Examine the instructions in docker-compose.yaml to setup the docker correctly, i.e., setup the correct UID and GID.

Step 1: Get the docker

We provide two options for obtaining the docker image. Please choose one of the methods listed below.

Option 1. Pull pre-built image from docker hub

We provide a pre-built image on dockerhub
```
docker-compose pull
```

Option 2. Build docker image from source

Build the timeloop-accelergy infrastructure docker

cd docker/accelergy-timeloop-infrastructure
make

Build the pytorch docker (which uses the timeloop-accelergy infrastructure as a basis)

cd ../timeloop-accelergy-pytorch
make
cd ../../  # go back to root directory of the repo

To check if the image is obtained successfully, please do docker image ls and you should see mitdlh/timeloop-accelergy-pytorch with a tag name micro22-artifact listed.

Step 2: Start the docker

Run docker-compose up. You should see the docker being setup.
This docker uses Jupyter notebooks, and you will see an URL once the docker is up. Please copy and paste the 127.0.0.1 URL to a web browser of your choice to access the workspace.
If you are experiencing any issues when bringing the page up, please try the tourble shooting notes in docker-compose.yaml.

Step 3: Run experiments in the docker

We provide a jupyter notebook for the experiments. Please navigate to workspace/2022.micro.artifact/notebook to run the experiments. Each cell in the notebook provides the background, instructions, and commands to run each evaluation with provided scripts.

For each experiment, we give a very conservative estiamtion of how long the sweeping will take. The input specifications and related scripts can be found in workspace/2022.micro.artifact/evaluation_setups. The easiest way to validate the outputs is to compare the generated figure/table to the figure/table in the paper, but we do provide a ref_outputs folder for each evaluation for more detailed comparison of results if necessary.

Accelergy-Project/micro22-sparseloop-artifact