Picotron is a minimalist, hackable distributed training framework designed for educational purposes, enabling users to learn and experiment with 4D parallelism (Data, Tensor, Pipeline, Context) for large language models. It offers a simplified codebase, making complex distributed training concepts accessible to researchers and students.

How It Works

Picotron implements 4D parallelism by breaking down model training across data, tensor, pipeline, and context dimensions. This approach allows for efficient distribution of large models and datasets across multiple GPUs, facilitating training of models that would otherwise be too large for single devices. The framework prioritizes code readability and simplicity, with core components like train.py and parallelism strategies under 300 lines each.

Quick Start & Requirements

• Install: pip install -e .
• Requirements: Hugging Face token for model downloads, GPU (CUDA recommended), torchrun for distributed execution. CPU execution is possible but slow.
• Links: [Tutorial Playlist](https://www.youtube.com/playlist?list=PLj0_g3_z04f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f_g9f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