A forwarding MPI implementation that can use any other MPI implementation via an MPI ABI

Overview

MPItrampoline

  • MPI wrapper library: GitHub CI
  • MPI trampoline library: GitHub CI
  • MPI integration tests: GitHub CI

MPI is the de-facto standard for inter-node communication on HPC systems, and has been for the past 25 years. While highly successful, MPI is a standard for source code (it defines an API), and is not a standard defining binary compatibility (it does not define an ABI). This means that applications running on HPC systems need to be compiled anew on every system. This is tedious, since the software that is available on every HPC system is slightly different.

This project attempts to remedy this. It defines an ABI for MPI, and provides an MPI implementation based on this ABI. That is, MPItrampoline does not implement any MPI functions itself, it only forwards them to a "real" implementation via this ABI. The advantage is that one can produce "portable" applications that can use any given MPI implementation. For example, this will make it possible to build external packages for Julia via Yggdrasil that run efficiently on almost any HPC system.

A small and simple MPIwrapper library is used to provide this ABI for any given MPI installation. MPIwrapper needs to be compiled for each MPI installation that is to be used with MPItrampoline, but this is quick and easy.

Successfully Tested

  • Debian 11.0 via Docker (MPICH; arm32v5, arm32v7, arm64v8, mips64le, ppc64le, riscv64; C/C++ only)
  • Debian 11.0 via Docker (MPICH; i386, x86-64)
  • macOS laptop (MPICH, OpenMPI; x86-64)
  • macOS via Github Actions (OpenMPI; x86-64)
  • Ubuntu 20.04 via Docker (MPICH; x86-64)
  • Ubuntu 20.04 via Github Actions (MPICH, OpenMPI; x86-64)
  • Blue Waters, HPC system at the NCSA (Cray MPICH; x86-64)
  • Graham, HPC system at Compute Canada (Intel MPI; x86-64)
  • Marconi A3, HPC system at Cineca (Intel MPI; x86-64)
  • Niagara, HPC system at Compute Canada (OpenMPI; x86-64)
  • Summit, HPC system at ORNL (Spectrum MPI; IBM POWER 9)
  • Symmetry, in-house HPC system at the Perimeter Institute (MPICH, OpenMPI; x86-64)

Workflow

Preparing an HPC system

Install MPIwrapper, wrapping the MPI installation you want to use there. You can install MPIwrapper multiple times if you want to wrap more than one MPI implementation.

This is possibly as simple as

cmake -S . -B build -DMPIEXEC_EXECUTABLE=mpiexec -DCMAKE_BUILD_TYPE=RelWithDebInfo -DCMAKE_INSTALL_PREFIX=$HOME/mpiwrapper
cmake --build build
cmake --install build

but nothing is ever simple on an HPC system. It might be necessary to load certain modules, or to specify more cmake MPI configuration options.

The MPIwrapper libraries remain on the HPC system, they are installed independently of any application.

Building an application

Build your application as usual, using MPItrampline as MPI library.

Running an application

At startup time, MPItrampoline needs to be told which MPIwrapper library to use. This is done via the environment variable MPITRAMPOLINE_LIB. You also need to point MPItrampoline's mpiexec to a respective wrapper created by MPIwrapper, using the environment variable MPITRAMPOLINE_MPIEXEC.

For example:

env MPITRAMPOLINE_MPIEXEC=$HOME/mpiwrapper/bin/mpiwrapper-mpiexec MPITRAMPOLINE_LIB=$HOME/mpiwrapper/lib/libmpiwrapper.so mpiexec -n 4 ./your-application

The mpiexec you run here needs to be the one provided by MPItrampoline.

Current state

MPItrampoline uses the C preprocessor to create wrapper functions for each MPI function. This is how MPI_Send is wrapped:

FUNCTION(int, Send,
         (const void *buf, int count, MT(Datatype) datatype, int dest, int tag,
          MT(Comm) comm),
         (buf, count, (MP(Datatype))datatype, dest, tag, (MP(Comm))comm))

Unfortunately, MPItrampoline does not yet wrap the Fortran API. Your help is welcome.

Certain MPI types, constants, and functions are difficult to wrap. Theoretically, there could be MPI libraries where it is not possible to implement the current MPI ABI. If you encounter this, please let me know -- maybe there is a work-around.

Comments
  • Add support for MPI profiling interface

    Add support for MPI profiling interface

    Each standard MPI function can be called with an MPI_ or PMPI_ prefix (quoting from https://www.open-mpi.org/faq/?category=perftools#PMPI), I think MPItrampoline doesn't currently support the PMPI_ calls.

    opened by ocaisa 6
  • Supporting `MPIX_Query_cuda_support()`

    Supporting `MPIX_Query_cuda_support()`

    While not part of the standard, MPIX_Query_cuda_support() is available in a number of MPI implementations (see https://github.com/pmodels/mpich/pull/4741). It's also being used by a number of applications (and hopefully that will grow, see my issue at https://github.com/lammps/lammps/issues/3140 which links back to the support in GROMACS). This would be a valuable inclusion in MPItrampoline since it would then be able to handle the runtime detection of CUDA support in the MPI implementation.

    opened by ocaisa 6
  • Allow overriding default compilation options

    Allow overriding default compilation options

    Currently default compilation options are set during the build of MPItrampoline, it would probably be useful to be able to fully override these, e.g.,

    exec ${MPITRAMPOLINE_CC:[email protected]_C_COMPILER@} ${CFLAGS:-"@CMAKE_C_FLAGS@"} [email protected]_INSTALL_PREFIX@/@CMAKE_INSTALL_INCLUDEDIR@ @LINK_FLAGS@ [email protected]_INSTALL_PREFIX@/@CMAKE_INSTALL_LIBDIR@ -Wl,-rpath,@CMAKE_INSTALL_PREFIX@/@CMAKE_INSTALL_LIBDIR@ "$@" -lmpi -ldl
    
    opened by ocaisa 5
  • Allow use of a fallback/default value for `MPITRAMPOLINE_MPIEXEC`

    Allow use of a fallback/default value for `MPITRAMPOLINE_MPIEXEC`

    It's possible to configure a default MPI library with -DMPITRAMPOLINE_DEFAULT_LIB=XXX, it would be good to be able to also configure a default mpiexec (-DMPITRAMPOLINE_DEFAULT_MPIEXEC=XXX) so that one can have a fully functional fallback in place at build time.

    opened by ocaisa 3
  • Incomplete installation

    Incomplete installation

    Hello ! I am looking at installing MPItrampoline, and following the steps outlined in the README.md, I cannot access files later referenced.

    For instance, on Summit at ORNL, using the following script:

    INSTALLDIR=$HOME/mpiwrapper
    
    module load cmake/3.18
    module load gcc
    
    cmake -S . -B build -DMPIEXEC_EXECUTABLE=mpiexec \
                                   -DCMAKE_BUILD_TYPE=RelWithDebInfo \
                                   -DCMAKE_INSTALL_PREFIX=$INSTALLDIR
    cmake --build build
    cmake --install build
    

    The following installation is generated:

    $ tree mpiwrapper/
    mpiwrapper/
    |-- bin
    |   |-- mpicc
    |   |-- mpicxx
    |   |-- mpiexec
    |   |-- mpifc
    |   `-- mpifort
    |-- include
    |   |-- mpi.h
    |   |-- mpi.mod
    |   |-- mpi_declarations.h
    |   |-- mpi_declarations_fortran.h
    |   |-- mpi_declarations_fortran90.h
    |   |-- mpi_defaults.h
    |   |-- mpi_f08.mod
    |   |-- mpi_version.h
    |   |-- mpiabi.h
    |   |-- mpiabif.h
    |   |-- mpif.h
    |   `-- mpio.h
    |-- lib
    |   |-- cmake
    |   |   `-- MPItrampoline
    |   |       |-- MPItrampolineConfig.cmake
    |   |       |-- MPItrampolineConfigVersion.cmake
    |   |       |-- MPItrampolineTargets-relwithdebinfo.cmake
    |   |       `-- MPItrampolineTargets.cmake
    |   `-- pkgconfig
    |       `-- MPItrampoline.pc
    `-- lib64
        |-- libmpi.a
        `-- libmpifort.a
    
    7 directories, 24 files
    

    The README.md dictates to use the wrapped libraries, but no shared libraries are available here. I looked through the options of the CMakeLists.txt but the only one defined in the project is the fortran flag.

    Am I missing something ?

    opened by spoutn1k 2
  •  Issues building Global Arrays

    Issues building Global Arrays

    I'm trying to build the Global Arrays library with MPItrampoline and have run into some issues. This package is a dependency for Molpro and several other computational chemistry applications. Any assistance that you can provide to get it working would be greatly appreciated.

    The compilation fails at https://github.com/GlobalArrays/ga/blob/f4016b869dfd1a2b2856f74a73dd9452dbbc8ae4/comex/src-mpi-pr/comex.c#L4968 with the error message:

    libtool: compile:  mpicc -DHAVE_CONFIG_H -I. -I./src-common -I./src-mpi-pr -g -O2 -MT src-mpi-pr/comex.lo -MD -MP -MF src-mpi-pr/.deps/comex.Tpo -c src-mpi-pr/comex.c -o src-mpi-pr/comex.o
    src-mpi-pr/comex.c: In function ‘str_mpi_retval’:
    src-mpi-pr/comex.c:4932:9: error: case label does not reduce to an integer constant
             case MPI_SUCCESS       : msg = "MPI_SUCCESS"; break;
             ^
    

    Steps to reproduce:

    git clone -b develop https://github.com/GlobalArrays/ga
    cd ga
    ./autogen.sh
    ./configure --with-mpi-pr --with-blas=no --with-lapack=no --with-scalapack=no --disable-f77
    make
    

    I've tried both the develop and master branches.

    There are lots of configurations which can be used, we're most interested in the recommended port which uses MPI-1 with progress ranks (--with-mpi-pr) but I tried several other configurations without success.

    I'm not sure whether it's an MPItrampoline issue or whether it's non-standard use of MPI within Global Arrays.

    I've attached the full output from build build-ga.txt

    I've tried on

    • RHEL 7.9 with gcc 4.8.5
    • Ubuntu 22.04 with gcc 11.3.0
    opened by nick-wilson 9
  • Issues building CP2K

    Issues building CP2K

    I thought I would give this a full test with Fortran, and CP2K is a good benchmark for that. The build (v8.2) is failing with:

    /project/60005/easybuild/build/CP2K/8.2/gmtfbf-2021a/cp2k-8.2/exts/dbcsr/src/mpi/dbcsr_mpiwrap.F:1669:21:
    
     1669 |       CALL mpi_bcast(msg, msglen, MPI_LOGICAL, source, gid, ierr)
          |                     1
    ......
     3160 |       CALL mpi_bcast(msg, msglen, ${mpi_type1}$, source, gid, ierr)
          |                     2
    Error: Type mismatch between actual argument at (1) and actual argument at (2) (LOGICAL(4)/COMPLEX(4)).
    
    opened by ocaisa 24
  • Building shared and static libraries at once

    Building shared and static libraries at once

    Currently the default behaviour is to only build static libraries. It might be good build both static and shared libraries since then if libmpi.so is in the default search path it is not selected over the library from MPItrampoline (MPItrampoline would shadow libmpi.so and libmpi.a).

    opened by ocaisa 4
Releases(v5.2.0)
Owner
Erik Schnetter
Erik Schnetter
TRIQ implementation

TRIQ Implementation TF-Keras implementation of TRIQ as described in Transformer for Image Quality Assessment. Installation Clone this repository. Inst

Junyong You 115 Dec 30, 2022
HAR-stacked-residual-bidir-LSTMs - Deep stacked residual bidirectional LSTMs for HAR

HAR-stacked-residual-bidir-LSTM The project is based on this repository which is presented as a tutorial. It consists of Human Activity Recognition (H

Guillaume Chevalier 287 Dec 27, 2022
Generative Handwriting using LSTM Mixture Density Network with TensorFlow

Generative Handwriting Demo using TensorFlow An attempt to implement the random handwriting generation portion of Alex Graves' paper. See my blog post

hardmaru 686 Nov 24, 2022
A Python module for the generation and training of an entry-level feedforward neural network.

ff-neural-network A Python module for the generation and training of an entry-level feedforward neural network. This repository serves as a repurposin

Riadh 2 Jan 31, 2022
Official code for "Focal Self-attention for Local-Global Interactions in Vision Transformers"

Focal Transformer This is the official implementation of our Focal Transformer -- "Focal Self-attention for Local-Global Interactions in Vision Transf

Microsoft 486 Dec 20, 2022
Official Code for "Constrained Mean Shift Using Distant Yet Related Neighbors for Representation Learning"

CMSF Official Code for "Constrained Mean Shift Using Distant Yet Related Neighbors for Representation Learning" Requirements Python = 3.7.6 PyTorch

4 Nov 25, 2022
Solutions of Reinforcement Learning 2nd Edition

Solutions of Reinforcement Learning, An Introduction

YIFAN WANG 1.4k Dec 30, 2022
Revisting Open World Object Detection

Revisting Open World Object Detection Installation See INSTALL.md. Dataset Our n

58 Dec 23, 2022
Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"

GPT-GNN: Generative Pre-Training of Graph Neural Networks GPT-GNN is a pre-training framework to initialize GNNs by generative pre-training. It can be

Ziniu Hu 346 Dec 19, 2022
Project Aquarium is a SUSE-sponsored open source project aiming at becoming an easy to use, rock solid storage appliance based on Ceph.

Project Aquarium Project Aquarium is a SUSE-sponsored open source project aiming at becoming an easy to use, rock solid storage appliance based on Cep

Aquarist Labs 73 Jul 21, 2022
This is the official released code for our paper, The Emergence of Objectness: Learning Zero-Shot Segmentation from Videos

The-Emergence-of-Objectness This is the official released code for our paper, The Emergence of Objectness: Learning Zero-Shot Segmentation from Videos

44 Oct 08, 2022
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training @ KDD 2020

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training Original implementation for paper GCC: Graph Contrastive Coding for Graph Neural N

THUDM 274 Dec 27, 2022
pytorch implementation of GPV-Pose

GPV-Pose Pytorch implementation of GPV-Pose: Category-level Object Pose Estimation via Geometry-guided Point-wise Voting. (link) UPDATE A new version

40 Dec 01, 2022
Minimal PyTorch implementation of Generative Latent Optimization from the paper "Optimizing the Latent Space of Generative Networks"

Minimal PyTorch implementation of Generative Latent Optimization This is a reimplementation of the paper Piotr Bojanowski, Armand Joulin, David Lopez-

Thomas Neumann 117 Nov 27, 2022
Pyramid Scene Parsing Network, CVPR2017.

Pyramid Scene Parsing Network by Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, Jiaya Jia, details are in project page. Introduction This

Hengshuang Zhao 1.5k Jan 05, 2023
Codebase to experiment with a hybrid Transformer that combines conditional sequence generation with regression

Regression Transformer Codebase to experiment with a hybrid Transformer that combines conditional sequence generation with regression . Development se

International Business Machines 27 Jan 05, 2023
Where2Act: From Pixels to Actions for Articulated 3D Objects

Where2Act: From Pixels to Actions for Articulated 3D Objects The Proposed Where2Act Task. Given as input an articulated 3D object, we learn to propose

Kaichun Mo 69 Nov 28, 2022
Unsupervised Feature Loss (UFLoss) for High Fidelity Deep learning (DL)-based reconstruction

Unsupervised Feature Loss (UFLoss) for High Fidelity Deep learning (DL)-based reconstruction Official github repository for the paper High Fidelity De

28 Dec 16, 2022
[ECCV 2020] Reimplementation of 3DDFAv2, including face mesh, head pose, landmarks, and more.

Stable Head Pose Estimation and Landmark Regression via 3D Dense Face Reconstruction Reimplementation of (ECCV 2020) Towards Fast, Accurate and Stable

Remilia Scarlet 221 Dec 30, 2022
Pathdreamer: A World Model for Indoor Navigation

Pathdreamer: A World Model for Indoor Navigation This repository hosts the open source code for Pathdreamer, to be presented at ICCV 2021. Paper | Pro

Google Research 122 Jan 04, 2023