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121 lines
4.9 KiB
Markdown
121 lines
4.9 KiB
Markdown
# hipDNN
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> [!CAUTION]
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> **hipDNN is in the early stages of development. There is currently limited functionality available to execute graphs. See [Operation Support](./docs/OperationSupport.md) for reference.**
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> [!NOTE]
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> The published hipDNN documentation is available [here](https://rocm.docs.amd.com/projects/hipdnn/en/latest/index.html) in an organized, easy-to-read format, with search and a table of contents. The documentation source files reside in the `docs` folder of this repository. As with all ROCm projects, the documentation is open source. For more information on contributing to the documentation, see [Contribute to ROCm documentation](https://rocm.docs.amd.com/en/latest/contribute/contributing.html).
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## Overview
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hipDNN is a graph-based deep learning library for AMD GPUs that leverages a flexible plugin architecture to provide optimized implementations and utilities for various routines.
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---
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## Table of Contents
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- [Getting Started](#getting-started)
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- [Documentation](#documentation)
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- [User Guides](#user-guides)
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- [Developer Guides](#developer-guides)
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- [Testing](#testing)
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- [Project Structure](#project-structure)
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- [API Documentation](#api-documentation)
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- [Contributing](#contributing)
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---
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## Getting Started
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The fastest way to get started with hipDNN is to follow the [quick start steps in the build guide](./docs/Building.md#quick-start-guide).
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---
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## Documentation
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### User Guides
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- **[Building](./docs/Building.md)** - Prerequisites, build configurations, and platform-specific instructions
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- **[Consumer Quick Start](./docs/ConsumerQuickStart.md)** - Using an installed hipDNN in your CMake project
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- **[How-To](./docs/HowTo.md)** - Using hipDNN components and extending the framework
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- **[Environment Configuration](./docs/Environment.md)** - Runtime configuration and logging setup
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- **[Operation Support](./docs/OperationSupport.md)** - Currently supported operations and their status
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- **[Samples](./samples/README.md)** - Frontend usage examples
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- **[API Reference](#api-documentation)** - Doxygen-generated API documentation
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### Developer Guides
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- **[Design Overview](./docs/Design.md)** - Architecture and design descriptions and diagrams
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- **[Extending hipDNN](./docs/HowTo.md#extending-hipdnn)** - How to extend hipDNN functionality
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- **[Plugin Development](./docs/PluginDevelopment.md)** - Creating and using custom plugins for hipDNN
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- **[Roadmap](./docs/Roadmap.md)** - Feature priorities and development plans
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### Testing
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- **[Testing](./docs/Testing.md)** - Synopsis of testing information
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- **[Testing Strategy](./docs/testing/TestingStrategy.md)** - Specific testing approach
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- **[Test Plan](./docs/testing/TestPlan.md)** - Detailed test planning
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- **[Test Run Template](./docs/testing/TestRunTemplate.md)** - Guidelines for test execution
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---
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## Project Structure
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hipDNN is organized into several key components. For detailed architecture descriptions, see the [Design Overview](./docs/Design.md).
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| Component | Description |
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| **[Backend](./backend/)** | Core shared library providing C API for operation graphs and managing plugins |
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| **[Data SDK](./data_sdk/)** | Header-only library with shared types, tensor utilities, logging, and the engine name registry |
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| **[Flatbuffers SDK](./flatbuffers_sdk/)** | Header-only library with FlatBuffers schemas, generated headers, graph wrappers, and optional JSON helpers |
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| **[Frontend](./frontend/)** | Header-only C++ API wrapper around the backend |
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| **[Plugin SDK](./plugin_sdk/)** | Header-only library for plugin development |
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| **[Samples](./samples/)** | Example implementations demonstrating hipDNN usage |
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| **[Tests](./tests/)** | Tests for the public API (incl. frontend integration tests) |
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| **[Tools](./tools/)** | Experimental utilities (e.g., benchmarking, engine listing) — subject to change |
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> [!NOTE]
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> Official hipDNN plugins can be found in the [dnn-providers](../../../dnn-providers/) folder (e.g., [MIOpen Plugin](../../../dnn-providers/miopen-provider/)).
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### Docker Support
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See [Docker README](./dockerfiles/README.md) for containerized development environments.
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---
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## API Documentation
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hipDNN includes Doxygen-generated API documentation for the public C++ frontend.
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### Building the Documentation
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1. Install Doxygen:
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```bash
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# Ubuntu/Debian
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sudo apt-get install doxygen
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```
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For Windows, download the installer from [doxygen.nl/download](https://www.doxygen.nl/download.html).
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2. Generate the documentation:
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```bash
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cd <project-root>
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doxygen Doxyfile
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```
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3. Open the generated documentation:
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```bash
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# Linux
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xdg-open build/docs/html/index.html
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# Windows
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start build\docs\html\index.html
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```
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The documentation covers the frontend API including:
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- Graph construction and execution
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- Tensor and operation attributes
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- Engine configuration and knobs
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- Error handling
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---
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## Contributing
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For information about contributing to the hipDNN project, please see the [Contributing Guide](./CONTRIBUTING.md).
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