.. meta::
   :description: How to use ROCm for high-performance computing (HPC).
   :keywords: ROCm, AI, high performance computing, HPC, science, scientific

******************
Using ROCm for HPC
******************

The ROCm open-source software stack is optimized to extract high-performance
computing (HPC) workload performance from AMD Instinct™ GPUs
while maintaining compatibility with industry software frameworks.

ROCm enhances support and access for developers by providing streamlined and
improved tools that significantly increase productivity. Being open-source, ROCm
fosters innovation, differentiation, and collaboration within the developer
community, making it a powerful and accessible solution for leveraging the full
potential of AMD GPUs' capabilities in diverse computational
applications.

* For more information, see :doc:`What is ROCm? <../../what-is-rocm>`.

* For guidance on installing ROCm, see :doc:`rocm-install-on-linux:index`. See
  the :doc:`Compatibility matrix <../../compatibility/compatibility-matrix>` for details on hardware
  and operating system support.

Some of the most popular HPC frameworks are part of the ROCm platform, including
those to help parallelize operations across multiple GPUs and servers,
handle memory hierarchies, and solve linear systems.

.. image:: ../../data/how-to/rocm-for-hpc/hpc-stack-2024_6_20.png
   :align: center
   :alt: Software and hardware ecosystem surrounding ROCm and AMD Instinct for HPC

The following catalog of GPU-accelerated solutions includes a vast set of
platform-compatible HPC applications, including those for astrophysics, climate
and weather, computational chemistry, computational fluid dynamics, earth
science, genomics, geophysics, molecular dynamics, and physics computing.

Refer to the resources in the following table for instructions on building,
running, and deploying these applications on ROCm-capable systems with AMD
Instinct GPUs. Each build container provides parameters to specify
different source code branches, release versions of ROCm, OpenMPI, UCX, and
Ubuntu versions.

.. _hpc-apps:

..
   Reduce font size of HPC app descriptions slightly.

.. raw:: html

   <style>
     #hpc-apps-table tr td:last-child {
       font-size: 0.9rem;
     }
   </style>

.. container::
   :name: hpc-apps-table

   .. list-table::
      :header-rows: 1
      :stub-columns: 1
      :widths: 2 2 5

      * - Application domain
        - HPC application
        - Description

      * - Physics
        - `Chroma <https://github.com/amd/InfinityHub-CI/tree/main/chroma/>`_
        - The Chroma package supports data-parallel programming constructs for lattice
          field theory and in particular lattice QCD. It uses the SciDAC QDP++ data-parallel
          programming (in C++) that presents a single high-level code image to the user,
          but can generate highly optimized code for many architectural systems including
          single node workstations, multi and many-core nodes, clusters of nodes via
          QMP, and classic vector computers.

      * -
        - `Grid <https://github.com/amd/InfinityHub-CI/tree/main/grid/>`_
        - Grid is a library for lattice QCD calculations that employs a high-level data parallel
          approach while using a number of techniques to target multiple types of parallelism.
          The library currently supports MPI, OpenMP, and short vector parallelism. The SIMD
          instruction sets covered include SSE, AVX, AVX2, FMA4, IMCI, and AVX512. Recent
          releases expanded this support to include GPU offloading.

      * -
        - `MILC <https://github.com/amd/InfinityHub-CI/tree/main/milc/>`_
        - The MILC Code is a set of research codes developed by MIMD Lattice Computation
          (MILC) collaboration for doing simulations of four dimensional SU(3) lattice gauge
          theory on MIMD parallel machines scaling from single-processor workstations
          to HPC systems. The MILC Code is publicly available for research purposes.
          Publications of work done using this code or derivatives of this code should
          acknowledge this use.

      * - 
        - `QUDA <https://github.com/amd/InfinityHub-CI/tree/main/quda>`_
        - Library designed for efficient lattice QCD computations on
          GPUs. It includes optimized Dirac operators and a variety of
          fermion solvers and conjugate gradient (CG) implementations, enhancing
          performance and accuracy in lattice QCD simulations.

      * -
        - `PIConGPU <https://github.com/amd/InfinityHub-CI/tree/main/picongpu>`_
        - PIConGPU (Particle-in-cell on Graphics Processing Units) is an Open Source
          simulations framework for plasma and laser-plasma physics used to develop
          advanced particle accelerators for radiation therapy of cancer, high energy
          physics and photon science.

      * - Astrophysics
        - `Cholla <https://github.com/amd/InfinityHub-CI/tree/main/cholla/>`_
        - An astrophysical simulation code developed for the extreme environments
          encountered in astrophysical systems.

      * - Geophysics
        - `SPECFEM3D Cartesian <https://github.com/amd/InfinityHub-CI/tree/main/specfem3d>`_
        - SPECFEM3D Cartesian simulates acoustic (fluid), elastic (solid), coupled
          acoustic/elastic, poroelastic or seismic wave propagation in any type of
          conforming mesh of hexahedra (structured or not.) It can, for instance,
          model seismic waves propagating in sedimentary basins or any other
          regional geological model following earthquakes. It can also be used
          for non-destructive testing or for ocean acoustics.

      * - Molecular dynamics
        - `Amber <https://github.com/amd/InfinityHub-CI/tree/main/amber>`_
        - Amber is a suite of biomolecular simulation programs. It is a set of molecular mechanical force fields for
          simulating biomolecules. Amber is also a package of molecular simulation
          programs which includes source code and demos.

      * -
        - `GROMACS with HIP (AMD implementation) <https://github.com/amd/InfinityHub-CI/tree/main/gromacs>`_
        - GROMACS is a versatile package to perform molecular dynamics, i.e.
          simulate the Newtonian equations of motion for systems with hundreds
          to millions of particles. This AMD container is based on a released
          version of GROMACS modified by AMD. This container only supports up
          to a 8 GPU configuration

      * -
        - `LAMMPS <https://github.com/amd/InfinityHub-CI/tree/main/lammps>`_
        - LAMMPS is a classical molecular dynamics code with a focus on materials
          modeling. It's an acronym for Large-scale Atomic/Molecular Massively
          Parallel Simulator.

      * - Computational fluid dynamics
        - `Ansys Fluent <https://github.com/amd/InfinityHub-CI/tree/main/ansys-fluent>`_
        - Ansys Fluent is an advanced computational fluid dynamics (CFD) tool for
          simulating and analyzing fluid flow, heat transfer, and related phenomena in complex systems.
          It offers a range of powerful features for detailed and accurate modeling of various physical
          processes, including turbulence, chemical reactions, and multiphase flows.

      * -
        - `NEKO <https://github.com/amd/InfinityHub-CI/tree/main/neko>`_
        - Neko is a portable framework for high-order spectral element flow simulations.
          Written in modern Fortran, Neko adopts an object-oriented approach, allowing
          multi-tier abstractions of the solver stack and facilitating various hardware
          backends ranging from general-purpose processors, CUDA and HIP enabled
          accelerators to SX-Aurora vector processors.

      * -
        - `Simcenter Star-CCM+ <https://github.com/amd/InfinityHub-CI/tree/main/siemens-star-ccm>`_
        - Simcenter Star-CCM+ is a comprehensive computational fluid dynamics (CFD) and multiphysics
          simulation tool developed by Siemens Digital Industries Software. It is designed to
          help engineers and researchers analyze and optimize the performance of products and
          systems across various industries.

      * - Quantum Monte Carlo Simulation
        - `QMCPACK <https://github.com/amd/InfinityHub-CI/tree/main/qmcpack>`_
        - QMCPACK is an open-source production-level many-body ab initio Quantum
          Monte Carlo code for computing the electronic structure of atoms, molecules, 2D
          nanomaterials and solids. The solid-state capabilities include metallic systems
          as well as insulators. QMCPACK is expected to run well on workstations through
          to the latest generation supercomputers. Besides high performance, particular
          emphasis is placed on code quality and reproducibility.

      * - Climate and weather
        - `MPAS <https://github.com/amd/InfinityHub-CI/tree/main/mpas>`_
        - The Model for Prediction Across Scales (MPAS) is a collaborative project for
          developing atmosphere, ocean, and other earth-system simulation components
          for use in climate, regional climate, and weather studies.

      * - Energy, Oil, and Gas
        - `DevitoPRO <https://github.com/amd/InfinityHub-CI/tree/main/devitopro>`_
        - DevitoPRO is an advanced extension of the open-source Devito platform with added
          features tailored for high-demand production workflows. It supports
          high-performance computing (HPC) needs, especially in seismic imaging and inversion.
          It is used to perform optimized finite difference (FD) computations
          from high-level symbolic problem definitions. DevitoPro performs automated
          code generation and Just-In-time (JIT) compilation based on symbolic equations
          defined in SymPy to create and execute highly optimized Finite Difference stencil
          kernels on multiple computer platforms.

      * - Benchmark
        - `rocHPL <https://github.com/amd/InfinityHub-CI/tree/main/rochpl>`_
        - HPL, or High-Performance Linpack, is a benchmark which solves a uniformly
          random system of linear equations and reports floating-point execution rate.

      * -
        - `rocHPL-MxP <https://github.com/amd/InfinityHub-CI/tree/main/hpl-mxp>`_
        - Benchmark that highlights the convergence of HPC and AI workloads by
          solving a system of linear equations using novel, mixed-precision
          algorithms.

      * -
        - `HPCG <https://github.com/amd/InfinityHub-CI/tree/main/hpcg>`_
        - HPCG, or the High Performance Conjugate Gradient Benchmark complements
          the High Performance LINPACK (HPL) benchmark. The computational and data
          access patterns of HPCG are designed to closely match a broad set of important
          applications not represented by HPL, and to incentivize computer system
          designers to invest in capabilities that will benefit the collective performance
          of these applications.

      * - Tools and libraries
        - `AMD ROCm with OpenMPI container <https://github.com/amd/InfinityHub-CI/tree/main/base-gpu-mpi-rocm-docker>`_
        - Base container for GPU-aware MPI with ROCm for HPC applications. This
          project provides a boilerplate for building and running a Docker
          container with ROCm supporting GPU-aware MPI implementations using
          OpenMPI or UCX.
      
      * - 
        - `AMD ROCm with MPICH container <https://github.com/amd/InfinityHub-CI/tree/main/base-mpich-rocm-docker>`_
        - Base container for GPU-aware MPI with ROCm for HPC applications. This
          project provides a boilerplate for building and running a Docker
          container with ROCm supporting GPU-aware MPI implementations using MPICH.

      * - 
        - `AMD ROCm with Conda Environment Container <https://github.com/amd/InfinityHub-CI/tree/main/conda-rocm-environment>`_
        - Container recipe that uses the `base-gpu-mpi-rocm-docker` as the base and adds Conda. The container can be used as a base for applications that require conda applications.
      
      * -
        - `Kokkos <https://github.com/amd/InfinityHub-CI/tree/main/kokkos>`_
        - Kokkos is a programming model in C++ for writing performance portable
          applications for use across HPC platforms. It provides abstractions for both
          parallel execution of code and data management. Kokkos is designed to target
          complex node architectures with N-level memory hierarchies and multiple types
          of execution resources.

      * -
        - `PyFR <https://github.com/amd/InfinityHub-CI/tree/main/pyfr>`_
        - PyFR is an open-source Python based framework for solving advection-diffusion
          type problems on streaming architectures using the Flux Reconstruction approach of
          Huynh. The framework is designed to solve a range of governing systems on mixed
          unstructured grids containing various element types. It is also designed to target a
          range of hardware platforms via use of an in-built domain specific language derived
          from the Mako templating engine.

      * -
        - `RAJA <https://github.com/amd/InfinityHub-CI/tree/main/raja>`_
        - RAJA is a library of C++ software abstractions, primarily developed at Lawrence
          Livermore National Laboratory (LLNL), that enables architecture and programming
          model portability for HPC applications.

      * -
        - `Trilinos <https://github.com/amd/InfinityHub-CI/tree/main/trilinos>`_
        - The Trilinos Project is an effort to develop algorithms and enabling technologies
          within an object-oriented software framework for the solution of large-scale,
          complex multi-physics engineering and scientific problems.

      * -
        - `VLLM <https://github.com/amd/InfinityHub-CI/tree/main/vllm>`_
        - The VLLM project helps to build a Dockerfile for performance testing of the LLAMA2 applications.
          This Dockerfile uses a base install that includes Ubuntu 20.04, ROCm 6.1.2 and Python 3.9. The container can host the LLAMA2 applications (LLMs) and requires some large input files for testing.

To learn about ROCm for AI applications, see :doc:`../rocm-for-ai/index`.
