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ROCm-Developer-Tools avatar

ROCm-Developer-Tools/HIP

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rocmdocs.amd.com/projects/HIP↗

HIP

HIP is a C++ GPU kernel language and cross-platform runtime designed for writing portable high-performance compute applications. It provides a programming interface that allows a single source codebase to execute on both AMD and NVIDIA GPU architectures.

The project functions as a compatibility layer that enables the conversion and migration of existing CUDA source code to run on AMD hardware. This is achieved through a syntax mapping that mirrors CUDA and a source-to-source translation process during compilation.

The toolkit covers the broader surface of cross-platform GPGPU development, including heterogeneous compute optimization and the creation of portable kernels. It utilizes a runtime abstraction to map unified API calls to vendor-specific driver libraries for memory and kernel management.

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Features

  • Portable Kernel Languages - Provides a C++ GPU kernel language for writing parallel compute kernels that target multiple hardware backends.
  • CUDA Source Converters - Converts existing NVIDIA CUDA source code into a compatible format to run on AMD hardware.
  • Cross-Vendor Compute Engines - Functions as a cross-platform runtime allowing compute applications to run on different GPU manufacturers.
  • GPU Kernel Development - Enables the development of single-source C++ kernels that execute on multiple GPU architectures.
  • Syntax Mapping Layers - Implements a language grammar that mirrors NVIDIA CUDA to simplify the porting of GPU kernels.
  • GPU Programming Runtimes - Supports writing single-source C++ code that runs on both AMD and NVIDIA GPUs.
  • Source-to-Source Compilers - Translates a shared C++ dialect into platform-specific GPU code during the compilation phase.
  • CUDA and HIP Code Generators - Facilitates the migration of existing CUDA source code to run on AMD hardware via the HIP interface.
  • CUDA Compatibility Layers - Provides a programming interface that allows NVIDIA CUDA source code to be converted and run on AMD hardware.
  • Runtime Abstraction Layers - Maps unified API calls to vendor-specific driver libraries for memory and kernel management.
  • Kernel Dispatchers - Provides a common interface to schedule GPU workloads across different hardware vendors.
  • Build-Time Dialect Mappings - Uses preprocessor macros and conditional headers to resolve hardware-specific types and function signatures at build time.
  • Heterogeneous Computing Libraries - Creates efficient GPU-accelerated applications that can be deployed across diverse hardware environments.
  • Cross-Platform Development - Provides a framework for developing high-performance compute kernels that remain portable across GPU vendors.
  • Parallel Programming Frameworks - C++ runtime API and kernel language for GPU acceleration.
4,362 stars·587 forks·C++·MIT·24 views

Star history

Star history chart for rocm-developer-tools/hipStar history chart for rocm-developer-tools/hip

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

Projects sharing features with HIP

These projects share indexed features with HIP. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
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    AITemplate is an ahead-of-time deep learning compiler that translates PyTorch neural networks into standalone C++ source code. It functions as a PyTorch to C++ compiler and a GPU kernel fusion engine, producing self-contained executable binaries that run inference without requiring a Python interpreter or deep learning framework runtime. The project generates optimized CUDA and HIP C++ code specifically for NVIDIA TensorCores and AMD MatrixCores. It focuses on maximizing throughput for half-precision floating-point operations through a system that combines multiple neural network operators in

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    ZLUDA is a middleware and translation engine designed to enable the execution of unmodified proprietary compute binaries on non-native graphics hardware. It functions as a compatibility layer that bridges vendor-specific compute interfaces with open standards, allowing software originally restricted to a single hardware ecosystem to operate on alternative graphics processing units. The project achieves this through a combination of dynamic library interception and runtime instruction translation. By replacing standard system libraries and mapping proprietary compute calls to open standards, t

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    taskflow/taskflow

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    Taskflow is a C++ task-parallel framework designed to build high-performance parallel workflows and complex dependency graphs. It provides a programming model that organizes computational work into directed acyclic graphs, enabling developers to manage concurrency, resource scheduling, and task dependencies across multi-core CPUs and GPU accelerators. The framework distinguishes itself through its ability to orchestrate heterogeneous systems, allowing for the integration of hardware-accelerated kernels and memory operations into unified execution pipelines. It supports dynamic runtime subflow

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Frequently asked questions

What does rocm-developer-tools/hip do?

HIP is a C++ GPU kernel language and cross-platform runtime designed for writing portable high-performance compute applications. It provides a programming interface that allows a single source codebase to execute on both AMD and NVIDIA GPU architectures.

What are the main features of rocm-developer-tools/hip?

The main features of rocm-developer-tools/hip are: Portable Kernel Languages, CUDA Source Converters, Cross-Vendor Compute Engines, GPU Kernel Development, Syntax Mapping Layers, GPU Programming Runtimes, Source-to-Source Compilers, CUDA and HIP Code Generators.

Which projects share features with rocm-developer-tools/hip?

Projects with overlapping indexed features include: facebookincubator/aitemplate — AITemplate is an ahead-of-time deep learning compiler that translates PyTorch neural networks into standalone C++… rocm/rocm. vosen/zluda — ZLUDA is a middleware and translation engine designed to enable the execution of unmodified proprietary compute… taskflow/taskflow — Taskflow is a C++ task-parallel framework designed to build high-performance parallel workflows and complex dependency… google/j2objc — j2objc is a source-to-source compiler and transpiler that converts Java source code into Objective-C. It functions as… scala-js/scala-js — Scala.js is a compiler and cross-platform language toolchain that transforms Scala source code into JavaScript or…