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Add "Using ROCm for HPC" guide (#3302)

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* Add ROCm for HPC

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.. meta::
:description: How to use ROCm for HPC
:keywords: ROCm, AI, high performance computing, HPC
******************
Using ROCm for HPC
******************
The ROCm open-source software stack is optimized to extract high-performance
computing (HPC) workload performance from AMD Instinct™ accelerators
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 accelerators' 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/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 accelerators 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 accelerators. 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
instructions 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.
* -
- `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
- `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
- `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.
* -
- `nekRS <https://github.com/amd/InfinityHub-CI/tree/main/nekrs>`_
- nekRS is an open-source Navier Stokes solver based on the spectral element
method targeting classical processors and accelerators like GPUs.
* - Computational chemistry
- `QUDA <https://github.com/amd/InfinityHub-CI/tree/main/quda>`_
- Library designed for efficient lattice QCD computations on
accelerators. It includes optimized Dirac operators and a variety of
fermion solvers and conjugate gradient (CG) implementations, enhancing
performance and accuracy in lattice QCD simulations.
* - Electronic structure
- `CP2K <https://github.com/amd/InfinityHub-CI/tree/main/cp2k>`_
- CP2K is a quantum chemistry and solid state physics software package that can
perform atomistic simulations of solid state, liquid, molecular, periodic, material,
crystal, and biological systems. This AMD container, based on a released version
of CP2K, is an AMD beta version with ongoing optimizations.
* - 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.
* - 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.
This documentation supports the implementation of the HPL benchmark on
top of AMD's ROCm platform.
* -
- `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
- `ROCm with GPU-aware MPI 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.
* -
- `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.
To learn about ROCm for AI applications, see :doc:`../rocm-for-ai/index`.