# Overall Architecture This document describes the overall architecture of MindSpore. [![View Source On Gitee](./_static/logo_source.png)](https://gitee.com/mindspore/docs/blob/r0.3/docs/source_en/architecture.md) The MindSpore framework consists of the Frontend Expression layer, Graph Engine layer, and Backend Runtime layer. ![architecture](./images/architecture.png) - MindSpore Frontend Expression layer This layer contains Python APIs, MindSpore intermediate representation (IR), and graph high level optimization (GHLO). - Python APIs provide users with a unified API for model training, inference, and export, and a unified API for data processing and format transformation. - GHLO includes optimization irrelevant to hardware (such as dead code elimination), auto parallel, and auto differentiation. - MindSpore IR provides unified intermediate representations, based on which MindSpore performs pass optimization. - MindSpore Graph Engine layer This layer contains graph low level optimization (GLLO) and graph execution. - GLLO includes hardware-related optimization and in-depth optimization related to the combination of hardware and software, such as operator fusion and buffer fusion. - Graph execution provides communication APIs required for offline graph execution and distributed training. - MindSpore Backend Runtime layer This layer contains the efficient running environments on the cloud, edge and device.