Skip to content

Latest commit

 

History

History
176 lines (128 loc) · 4.26 KB

README.md

File metadata and controls

176 lines (128 loc) · 4.26 KB
Raw

Twister2Flow

Designing a dataflow pipeline to support high performance deep learning in Twister2. This is an experimental version of the initial High Performance Deep Learning Connect of Twister2.

Pytorch Setup On RHEL7

Set Up Romeo (RHEL7) For Pytorch Parallel Compatibility

module load anaconda
module load cuda/10.0
module load cudnn/10.0-v7.4.1
module load gcc/6.4.0
export CUDNN_INCLUDE_DIR=/opt/cudnn-10.0-linux-x64-v7.4.1/cuda/include
export CUDNN_LIB_DIR=/opt/cudnn-10.0-linux-x64-v7.4.1/cuda/lib64
conda create -n py36 python=3.6
source activate py36
export CMAKE_PREFIX_PATH="$(dirname $(which conda))/../"
export CMAKE_PREFIX_PATH="/opt/gcc-6.4.0;$CMAKE_PREFIX_PATH"
conda install -c anaconda libgcc-ng libstdcxx-ng
conda install -c conda-forge openmpi
conda install numpy ninja pyyaml mkl setuptools cmake cffi
conda install -c pytorch magma-cuda100
conda install -c mingfeima mkldnn
conda uninstall --force mkl
pip install mkl
pip install mkl_include
conda uninstall --force cmake
pip install cmake
chmod +x ~/.conda/envs/py36/lib/python3.6/site-packages/cmake/data/bin/*
git clone --recursive https://github.com/pytorch/pytorch
cd pytorch/
BUILD_TEST=0 python setup.py install

Credits

Allan Streib of Future Systems, Indiana University Bloomington designed the set up.

Setting Up RHEL7 (Romeo r-003)

module load anaconda
module load cuda/10.0
module load cudnn/10.0-v7.4.1
module load gcc/6.4.0
export CUDNN_INCLUDE_DIR=/opt/cudnn-10.0-linux-x64-v7.4.1/cuda/include
export CUDNN_LIB_DIR=/opt/cudnn-10.0-linux-x64-v7.4.1/cuda/lib64

Note

Private Note: This is for running in r-003 RHEL7

source activate ENV1

Running Examples

RHEL7 Compatible

mpirun -n <parallelism> python3 mnist/mnist_dist_rhel7.py

Supporting Dataflow Operations

  1. File Systems oriented dataflow operations
  2. Remote Memory Access (Work In Progress)

Supporting Frameworks

  1. Twister2 (JVM Oriented Big Data Toolkit)
  2. Pytorch (Deep Learning Library)
  3. Python3

Install

python3 -m pip install --index-url https://test.pypi.org/simple/ --no-deps twister2flow-test

Bootstrap Task Executor

python3 bootstrap/PytorchJobSubmitter.py\ 
    --script examples/disk/PytorchMnistDist.py\ 
    --executor python3\ 
    --parallelism 4 --hostfile hostfile

Example Disk-based Dataflow

from twister2flow.twister2.pipeline import PipelineGraph
from twister2flow.twister2.task.Twister2Task import Twister2Task
from twister2flow.twister2.task.PytorchTask import PytorchTask
from twister2flow.twister2.task.PythonTask import PythonTask

plg = PipelineGraph.PipelineGraph(name="UNNAMED_TASK")

download_task = PythonTask(name="download_task")
download_task.set_command("python3")
download_task.set_script_path(script_path="MnistDownload.py")
download_task.set_exec_path(exec_path=None)

twister2_task = Twister2Task(name="t2_task")
twister2_task.set_command()
twister2_task.set_script_path(script_path="Twister2PytorchMnist.py")
twister2_task.set_exec_path(exec_path=None)

pytorch_task = PytorchTask(name="pytorch_task")
pytorch_task.set_command()
pytorch_task.set_script_path(script_path="PytorchMnistDist.py")
pytorch_task.set_exec_path(exec_path=None)

plg.add_task(download_task)
plg.add_task(twister2_task)
plg.add_task(pytorch_task)


print(str(plg))

plg.execute()

Running example

cd examples/disk
python3 Twister2FlowWithDisk.py

Run In-Memory Example

from twister2flow.twister2.pipeline import PipelineGraph
from twister2flow.twister2.task.Twister2Task import Twister2Task
from twister2flow.twister2.task.PythonTask import PythonTask

plg = PipelineGraph.PipelineGraph(name="UNNAMED_TASK")

download_task = PythonTask(name="download_task")
download_task.set_command("python3")
download_task.set_script_path(script_path="MnistDownload.py")
download_task.set_exec_path(exec_path=None)

twister2_task = Twister2Task(name="t2_task")
twister2_task.set_command("twister2 submit standalone python")
twister2_task.set_script_path(script_path="Twister2DistMnist.py")
twister2_task.set_exec_path(exec_path=None)

plg.add_task(download_task)
plg.add_task(twister2_task)

print(str(plg))

plg.execute()
cd examples/memory
python3 Twister2FlowWithMemory.py