README.md

ISC 24 - Tutorial on Distributed Training of Deep Neural Networks

All the code for the hands-on exercies can be found in this repository.

Table of Contents

• Setup
• Basics of Model Training
• Data Parallelism
• Tensor Parallelism
• Pipeline Parallelism

Setup

To request an account on Zaratan, please join slack at the link above, and fill this Google form.

We have pre-built the dependencies required for this tutorial on Zaratan. This will be activated automatically when you run the bash scripts.

The training dataset i.e. MNIST has also been downloaded in /scratch/zt1/project/isc/shared/data/MNIST.

Basics of Model Training

Using PyTorch

cd session_1_basics/
sbatch --reservation=isc2024 run.sh

Mixed Precision

MIXED_PRECISION=true sbatch --reservation=isc2024 run.sh

Activation Checkpointing

CHECKPOINT_ACTIVATIONS=true sbatch --reservation=isc2024 run.sh

Data Parallelism

Pytorch Distributed Data Parallel (DDP)

cd session_2_data_parallelism
sbatch --reservation=isc2024 run_ddp.sh

Zero Redundancy Optimizer (ZeRO)

sbatch --reservation=isc2024 run_deepspeed.sh

Intra-layer (Tensor) Parallelism

cd session_3_intra_layer_parallelism
sbatch --reservation=isc2024 run.sh

Inter-layer (Pipeline) Parallelism

cd session_4_inter_layer_parallelism
sbatch --reservation=isc2024 run.sh

Hybrid Inter-layer (Pipeline) + Data Parallelism

HYBRID_PARR=true sbatch --reservation=isc2024 run.sh