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67 lines
3.0 KiB
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67 lines
3.0 KiB
ReStructuredText
.. meta::
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:description: hipDNN (Deep Neural Network) is a graph-based library providing improved performance for deep learning workloads with AMD GPUs.
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:keywords: hipDNN, ROCm, documentation
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.. _what-is:
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******************
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What is hipDNN?
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******************
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hipDNN (Deep Neural Network) is a graph-based library that improves performance for deep learning workloads on AMD GPUs.
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hipDNN uses operation graphs as an intermediate representation for describing computations, allowing different backend engines to optimize and execute them efficiently.
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hipDNN provides an interface that follows established deep learning conventions and a plugin-based architecture, which allows advanced users to extend hipDNN without modifying the core library.
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.. note::
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hipDNN is in beta. Running production workloads is not recommended.
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hipDNN and the ROCm ecosystem
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=============================
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.. list-table::
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:widths: 3 3 5
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:header-rows: 1
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* - Layer
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- Component
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- Function
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* - Framework
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- PyTorch/TensorFlow
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- The high-level AI tools developers use.
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* - Interface
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- **hipDNN**
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- The portable API for deep learning operations.
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* - Engine selection and execution
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- Engine provider plugins
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- Matches fused graph operations with engines for optimized performance.
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* - Runtime
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- HIP
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- The translation layer between C++ and the GPU hardware.
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* - Hardware
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- AMD Instinct™ / Radeon™
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- The physical GPU.
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Features
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========
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- **Graph-based API**: Operations are expressed as computational graphs rather than individual function calls, enabling optimization opportunities.
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- **Plugin architecture**: Backend kernel engines are implemented through plugins, allowing extensibility without modifying the core library.
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- **Increased performance through fusion**: Multiple operations can be fused into single kernels for better performance.
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- **Industry-standard API**: Provides a familiar interface that matches established deep learning library conventions.
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Components
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==========
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- **Frontend**: A header-only C++ library that provides the industry-standard API for interacting with hipDNN. The frontend wraps the backend C API to provide a more user-friendly C++ interface.
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- **Backend**: A shared library that provides a C API for hipDNN. The backend is the core component of hipDNN. It acts as a plugin loader and manager, connecting problems to engines (provided via plugins) that can solve them.
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- **SDKs**: Header-only libraries that provide shared utilities and interfaces. hipDNN provides three SDKs: the Data SDK (graph schemas and data structures), Plugin SDK (plugin API and utilities), and Test SDK (testing utilities and CPU reference implementations).
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- **Plugins**: Plugins provide additional operational support or performance improvements.
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Engine provider plugins
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=======================
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hipDNN operations are implemented through provider plugins. Each provider plugin provides its own set of supported operations. See :ref:`plugin-support` for more information.
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