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Charm++

Build Status Documentation Status DOI

Introduction

Charm++ is a message-passing parallel language and runtime system. It is implemented as a set of libraries for C++, is efficient, and is portable to a wide variety of parallel machines. Source code is provided, and non-commercial use is free.

Getting the Latest Source

You can use anonymous Git access to obtain the latest Charm++ source code, as follows:

 $ git clone https://github.com/charmplusplus/charm

Build Configuration

Quick Start:

First-time users are encouraged to run the top-level build script and follow its lead:

$ ./build

Advanced Build Options:

First, you need to decide which version of Charm++ to use. The build script takes several command line options to compile Charm++. The command line syntax is:

 $ ./build <target> <version> [options ...]
                              [--basedir=dir] [--libdir=dir] [--incdir=dir]
                              [charmc-options ...]

For detailed help messages, pass -h or --help to the build script.

Required:

<target> specifies the parts of Charm++ to compile. The most often used <target> is charm++, which will compile the key Charm++ executables and runtime libraries. Other common targets are AMPI and LIBS, which build Adaptive MPI and Charm++ and all of its libraries, respectively. <version> defines the CPU, OS and communication layer of the machines. See "How to choose a <version>" below for details.

Optional:

<options> defines more detailed information of the compilations, including compilers, features to support, etc. See "How to choose <options>" below.

  • [--libdir=dir] specify additional lib paths for building Charm++.
  • [--incdir=dir] specify additional include paths for building Charm++.
  • [--basedir=dir] a shortcut to specify additional include and library paths for building Charm++, the include path is dir/include and library path is dir/lib.

Running build script, a directory of the name of combination of version and options like <version>-<option1>-<option2>-... will be created and the build script will compile Charm++ under this directory.

For example, on an ordinary Linux PC:

 $ ./build charm++ netlrts-linux-x86_64

will build Charm++ in the directory netlrts-linux-x86_64/. The communication defaults to UDP packets and the compiler to gcc.

For a more complex example, consider a shared-memory build with the Intel C++ compiler icc, where you want the communication to happen over TCP sockets:

 $ ./build charm++ netlrts-linux-x86_64 smp icc tcp

will build Charm++ in the directory netlrts-linux-x86_64-smp-tcp-icc/.

You can specify multiple options, however you can use at most one compiler option. The sequencing of options given to the build script should follow the rules:

  1. Compiler option should be at the end
  2. Other options are sorted alphabetically

How to choose a <version>:

Here is the table for choosing a correct build version. The default compiler in Charm++ is gcc/g++ on Linux and clang/clang++ on MacOS. However, one can use <options> to specify other compilers. See the detailed explanation of the <options> below.

(Note: this isn't a complete list. Run ./build for a complete listing)

Charm++ Version OS Communication Default Compiler
netlrts-linux-x86_64 Linux UDP GNU compiler
netlrts-darwin-x86_64 macOS UDP Clang C++ compiler
netlrts-win-x86_64 Windows UDP MS Visual C++
mpi-linux-x86_64 Linux MPI GNU compiler
multicore-linux-x86_64 Linux Shared memory GNU compiler
multicore-darwin-x86_64 macOS Shared memory Clang C++ compiler
gni-crayxc Linux GNI CC (whatever PrgEnv module is loaded)
gni-crayxe Linux GNI CC (whatever PrgEnv module is loaded)
verbs-linux-x86_64 Linux IB Verbs GNU compiler
ofi-linux-x86_64 Linux OFI GNU compiler
ucx-linux-x86_64 Linux UCX GNU compiler

To choose <version>, your choice is determined by two options:

  1. The way a parallel program written in Charm++ will communicate:

    • netlrts-: Charm++ communicates using the regular TCP/IP stack (UDP packets), which works everywhere but is fairly slow. Use this option for networks of workstations, clusters, or single-machine development and testing.
    • gni-, pamilrts-, verbs-, ofi-, ucx- : Charm++ communicates using direct calls to the machine's communication primitives. Use these versions on machines that support them for best performance.
    • mpi-: Charm++ communicates using MPI calls. This will work on almost every distributed machine, but performance is often worse than using the machine's direct calls referenced above.
    • multicore-: Charm++ communicates using shared memory within a single node. A version of Charm++ built with this option will not run on more than a single node.

  2. Your operating system/architecture:

    • linux-x86_64: Linux with AMD64 64-bit x86 instructions
    • win-x86_64: MS Windows with MS Visual C++ compiler
    • darwin-x86_64: Apple macOS
    • cray{xe/xc}: Cray XE/XC Supercomputer
    • linux-ppc64le: POWER/PowerPC

Your Charm++ version is made by concatenating the options, e.g.:

  • netlrts-linux-x86_64: Charm++ for a network of 64-bit Linux workstations compiled using g++.
  • gni-crayxc: Charm++ for Cray XC systems using the system compiler.

How to choose <options>:

<version> above defines the most important OS, CPU, and communication of your machine.

To use a different compiler or demand additional special feature support, you need to choose <options> from the following list (compilers may also be suffixed with a version number to use a specific version, e.g. gcc-7). Note that this list is merely a sampling of common options, please see the documentation for more information:

  • icc - Intel C/C++ compiler.

  • ifort - Intel Fortran compiler

  • xlc - IBM XLC compiler.

  • clang - Clang compiler.

  • mpicxx - Use MPI-wrappers for MPI builds.

  • pgcc - Portland Group's C++ compiler.

  • smp - Enable direct SMP support. An smp version communicates using shared memory within a process but normal message passing across processes and nodes. smp mode also introduces a dedicated communication thread for every process. Because of locking, smp may slightly impact non-SMP performance. Try your application to decide if enabling smp mode improves performance.

  • tcp - The netlrts- version communicates via UDP by default. The tcp option will use TCP instead. The TCP version of Charm++ is usually slower than UDP, but it is more reliable.

  • async - On PAMI systems, this option enables use of hardware communication threads. For applications with significant communication on large scale, this option typically improves performance.

  • regularpages - On Cray systems, Charm++'s default is to use hugepages. This option disables hugepages, and uses regular malloc for messages.

  • persistent - On Cray systems, this option enables use of persistent mode for

  • cxi - On HPE Slingshot-11 systems, this option enables use of Cassini extensions for communication. Usually autodetected and enabled where available.

  • pxshm - Use POSIX Shared Memory for communication between Charm++ processes within a shared-memory host.

  • syncft - Enable in-memory fault tolerance support in Charm++.

  • tsan - Compile Charm++ with support for Thread Sanitizer.

  • papi - Enable PAPI performance counters.

  • ooc - Build Charm++ with out-of-core execution features.

  • help - show supported options for a version. For example, for netlrts-linux-x86_64, running:

       $ ./build charm++ netlrts-linux-x86_64 help

    will give:

    Supported compilers: clang craycc gcc icc iccstatic msvc pgcc xlc xlc64 icx
Supported options: common cuda flang gfortran ifort local nolb omp ooc papi perftools persistent pgf90 pxshm smp syncft sysvshm tcp tsan

Building the Source

If you have downloaded a binary version of Charm++, you can skip this step -- Charm++ should already be compiled.

Once you have decided on a version, unpack Charm++, cd into charm/, and run

 $ ./build <target> <version> <opts>

<target> is one of:

  • charm++ The basic Charm++ language
  • AMPI An implementation of MPI on top of Charm++
  • LIBS Charm++, AMPI, and other libraries built on top of them

<version> is described above in the "How to choose a <version>" section.

<opts> are build-time options (such as the compiler or smp), or command line options passed to the charmc compiler script. Common compile time options such as -g, -O, -Ipath, -Lpath, -llib are accepted (these may vary depending on the compiler one has selected).

For example, on a Linux machine, you would run

 $ ./build charm++ netlrts-linux-x86_64 -O

This will construct a netlrts-linux-x86_64 directory, link over all the Charm++ source code into netlrts-linux-x86_64/tmp, build the entire Charm++ runtime system in netlrts-linux-x86_64/tmp, and link example programs into netlrts-linux-x86_64/examples.

Charm++ can be compiled with several optional features enabled or disabled. These include runtime error checking, tracing, interactive debugging, deterministic record-replay, and more. They can be controlled by passing flags of the form --enable-<featurename> or --disable-<featurename> to the build command:

 $ ./build charm++ netlrts-linux-x86_64 --disable-tracing

Production optimizations: Pass the configure option --with-production to ./build to turn on optimizations in Charm++/Converse. This disables most of the run-time checking performed by Converse and Charm++ runtime. This option should be used only after the program has been debugged. Also, this option disables Converse/Charm++ tracing mechanisms such as projections and summary.

Performance analysis: Pass the configuration option --enable-tracing to enable tracing and generation of logs for analysis with Projections. This is the recommended way to analyze performance of applications.

When Charm++ is built successfully, the directory structure under the target directory will look like:

netlrts-linux-x86_64/
   |
   ---  benchmarks/      # benchmark programs
   |
   ---  bin/             # all executables
   |
   ---  doc/             # documentations
   |
   ---  include/         # header files
   |
   ---  lib/             # static libraries
   |
   ---  lib_so/          # shared libraries
   |
   ---  examples/        # example programs
   |
   ---  tests/           # test programs
   |
   ---  tmp/             # Charm++ build directory

Building a Program

To make a sample program, cd into examples/charm++/NQueen/. This program solves the n queens problem-- find how many ways there are to arrange n queens on an n x n chess board such that none may attack another.

To build the program, type make. You should get an executable named nqueen.

Running a Program

Following the previous example, to run the program on two processors, type

 $ ./charmrun +p2 ./nqueen 12 6

This should run for a few seconds, and print out: There are 14200 Solutions to 12 queens. Time=0.109440 End time=0.112752

charmrun is used to provide a uniform interface to run charm programs. On some platforms, charmrun is just a shell script which calls the platform-specific start program, such as mpirun on MPI versions.

For the netlrts- version, charmrun is an executable which invokes ssh to start node programs on remote machines. You should set up a ~/.nodelist that enumerates all the machines you want to run jobs on, otherwise it will create a default ~/.nodelist for you that contains only localhost. Here is a typical .nodelist file:

group main ++shell /bin/ssh
host <machinename>

The default remote shell program is ssh, but you can define a different remote shell to start remote processes using the ++shell option. You should also make sure that ssh or your alternative can connect to these machines without password authentication. Just type following command to verify:

$ ssh <machinename> date

If this gives you current date immediately, your running environment with this node has been setup correctly.

For development purposes, the netlrts- version of charmrun comes with an easy-to-use ++local option. No remote shell invocation is needed in this case. It starts node programs right on your local machine. This could be useful if you just want to run program on only one machine, for example, your laptop. This can save you all the hassle of setting up ssh daemons. To use this option, just type:

 $ ./charmrun ++local ./nqueen 12 100 +p2

However, for best performance, you should launch one node program per processor.

Building Dynamic Libraries

In order to compile Charm++ into dynamic libraries, one needs to specify the --build-shared option to the Charm ./build script. Charm++'s dynamic libraries are compiled into the lib_so/ directory. Typically, they are generated with a .so suffix.

One can compile a Charm++ application linking against Charm++ dynamic libraries by linking with charmc's -charm-shared option. For example:

 $ charmc -o pgm pgm.o -charm-shared

You can then run the program as usual. Note that linking against Charm++ dynamic libraries produces much smaller binaries and takes much less linking time.

Contributing

The recommended way to contribute to Charm++ development is to open a pull request (PR) on GitHub. To open a pull request, create a fork of the Charm++ repo in your own space (if you already have a fork, make sure is it up-to-date), and then create a new branch off of the main branch.

GitHub provides a detailed tutorial on creating pull requests (https://docs.github.com/en/pull-requests/collaborating-with-pull-requests).

Each pull request must pass code review and CI tests before it can be merged by someone on the core development team. Our wiki contains additional information about pull requests (https://github.com/charmplusplus/charm/wiki/Working-with-Pull-Requests).

For More Information

The Charm++ documentation is at https://charm.readthedocs.io/

The Charm++ web page, with more information, more programs, and the latest version of Charm++, is at https://charmplusplus.org

The UIUC Parallel Programming Laboratory web page, with information on past and present research, is at https://charm.cs.illinois.edu

For questions, comments, suggestions, improvements, or bug reports, please create an issue or discussion on our GitHub, https://github.com/charmplusplus/charm

Authors

Charm++ was created and is maintained by the Parallel Programming Lab, in the Computer Science department at the University of Illinois at Urbana-Champaign. Our managing professor is Dr. L.V. Kale; students and staff have included (in rough time order) Wennie Shu, Kevin Nomura, Wayne Fenton, Balkrishna Ramkumar, Vikram Saletore, Amitabh B. Sinha, Manish Gupta, Attila Gursoy, Nimish Shah, Sanjeev Krishnan, Jayant DeSouza, Parthasarathy Ramachandran, Jeff Wright, Michael Lang, Jackie Wang, Fang Hu, Michael Denardo, Joshua Yelon, Narain Jagathesan, Zehra Sura, Krishnan Varadarajan, Sameer Paranjpye, Milind Bhandarkar, Robert Brunner, Terry Wilmarth, Gengbin Zheng, Orion Lawlor, Celso Mendes, Karthik Mahesh, Neelam Saboo, Greg Koenig, Sameer Kumar, Sayantan Chakravorty, Chao Huang, Chee Lee, Fillipo Gioachin, Isaac Dooley, Abhinav Bhatele, Aaron Becker, Ryan Mokos, Ramprasad Venkataraman, Gagan Gupta, Pritish Jetley, Lukasz Wesolowski, Esteban Meneses, Chao Mei, David Kunzman, Osman Sarood, Abhishek Gupta, Yanhua Sun, Ehsan Totoni, Akhil Langer, Cyril Bordage, Harshit Dokania, Prateek Jindal, Jonathan Lifflander, Xiang Ni, Harshitha Menon, Nikhil Jain, Vipul Harsh, Bilge Acun, Phil Miller, Seonmyeong Bak, Karthik Senthil, Juan Galvez, Michael Robson, Raghavendra Kanakagiri, Venkatasubrahmanian Narayanan. Nitin Bhat, and Justin Szaday. Current developers include: Eric Bohm, Ronak Buch, Eric Mikida, Sam White, Kavitha Chandrasekar, Jaemin Choi, Matthias Diener, Evan Ramos, Zane Fink, Pathikrit Ghosh, Maya Taylor, Aditya Bhosale, Mathew Jacob, Tom Vander Aa, Thomas Quinn, and Ritvik Rao.

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