All Projects → lanl → vpic

lanl / vpic

Licence: other
Vector Particle-In-Cell (VPIC) Project

Programming Languages

C++
36643 projects - #6 most used programming language
c
50402 projects - #5 most used programming language
shell
77523 projects
matlab
3953 projects
python
139335 projects - #7 most used programming language
CMake
9771 projects

Projects that are alternatives of or similar to vpic

ParallelUtilities.jl
Fast and easy parallel mapreduce on HPC clusters
Stars: ✭ 28 (-77.42%)
Mutual labels:  hpc, high-performance-computing, hpc-applications
Opencoarrays
A parallel application binary interface for Fortran 2018 compilers.
Stars: ✭ 151 (+21.77%)
Mutual labels:  hpc, high-performance-computing
julea
A Flexible Storage Framework for HPC
Stars: ✭ 25 (-79.84%)
Mutual labels:  hpc, high-performance-computing
blas-benchmarks
Timing results for BLAS (Basic Linear Algebra Subprograms) libraries in R
Stars: ✭ 24 (-80.65%)
Mutual labels:  hpc, high-performance-computing
t8code
Parallel algorithms and data structures for tree-based AMR with arbitrary element shapes.
Stars: ✭ 37 (-70.16%)
Mutual labels:  hpc, high-performance-computing
integrated-manager-for-lustre
Integrated Manager for Lustre
Stars: ✭ 64 (-48.39%)
Mutual labels:  hpc, high-performance
COBREXA.jl
Constraint-Based Reconstruction and EXascale Analysis
Stars: ✭ 21 (-83.06%)
Mutual labels:  hpc, high-performance
Batchtools
Tools for computation on batch systems
Stars: ✭ 127 (+2.42%)
Mutual labels:  hpc, high-performance-computing
Geopm
Global Extensible Open Power Manager
Stars: ✭ 57 (-54.03%)
Mutual labels:  hpc, high-performance-computing
Mfem
Lightweight, general, scalable C++ library for finite element methods
Stars: ✭ 667 (+437.9%)
Mutual labels:  hpc, high-performance-computing
Foundations of HPC 2021
This repository collects the materials from the course "Foundations of HPC", 2021, at the Data Science and Scientific Computing Department, University of Trieste
Stars: ✭ 22 (-82.26%)
Mutual labels:  hpc, hpc-applications
Sundials
SUNDIALS is a SUite of Nonlinear and DIfferential/ALgebraic equation Solvers. This is a mirror of current releases, and development will move here eventually. Pull requests are welcome for bug fixes and minor changes.
Stars: ✭ 194 (+56.45%)
Mutual labels:  hpc, high-performance-computing
hp2p
Heavy Peer To Peer: a MPI based benchmark for network diagnostic
Stars: ✭ 17 (-86.29%)
Mutual labels:  hpc, hpc-applications
CARE
CHAI and RAJA provide an excellent base on which to build portable codes. CARE expands that functionality, adding new features such as loop fusion capability and a portable interface for many numerical algorithms. It provides all the basics for anyone wanting to write portable code.
Stars: ✭ 22 (-82.26%)
Mutual labels:  hpc, hpc-applications
Tf Quant Finance
High-performance TensorFlow library for quantitative finance.
Stars: ✭ 2,925 (+2258.87%)
Mutual labels:  high-performance, high-performance-computing
Libflame
High-performance object-based library for DLA computations
Stars: ✭ 197 (+58.87%)
Mutual labels:  high-performance, high-performance-computing
Blis
BLAS-like Library Instantiation Software Framework
Stars: ✭ 859 (+592.74%)
Mutual labels:  high-performance, high-performance-computing
Nnpack
Acceleration package for neural networks on multi-core CPUs
Stars: ✭ 1,538 (+1140.32%)
Mutual labels:  high-performance, high-performance-computing
Blitz
Blitz++ Multi-Dimensional Array Library for C++
Stars: ✭ 257 (+107.26%)
Mutual labels:  hpc, high-performance
Dash
DASH, the C++ Template Library for Distributed Data Structures with Support for Hierarchical Locality for HPC and Data-Driven Science
Stars: ✭ 134 (+8.06%)
Mutual labels:  hpc, high-performance-computing

Vector Particle-In-Cell (VPIC) Project

Welcome to the legacy version of VPIC! The new version of VPIC, based on the Kokkos performance portable framework, is available here: https://github.com/lanl/vpic-kokkos. This legacy version is no longer under active development, and new users are encouraged to use the Kokkos version.

VPIC is a general purpose particle-in-cell simulation code for modeling kinetic plasmas in one, two, or three spatial dimensions. It employs a second-order, explicit, leapfrog algorithm to update charged particle positions and velocities in order to solve the relativistic kinetic equation for each species in the plasma, along with a full Maxwell description for the electric and magnetic fields evolved via a second- order finite-difference-time-domain (FDTD) solve. The VPIC code has been optimized for modern computing architectures and uses Message Passing Interface (MPI) calls for multi-node application as well as data parallelism using threads. VPIC employs a variety of short-vector, single-instruction-multiple-data (SIMD) intrinsics for high performance and has been designed so that the data structures align with cache boundaries. The current feature set for VPIC includes a flexible input deck format capable of treating a wide variety of problems. These include: the ability to treat electromagnetic materials (scalar and tensor dielectric, conductivity, and diamagnetic material properties); multiple emission models, including user-configurable models; arbitrary, user-configurable boundary conditions for particles and fields; user- definable simulation units; a suite of "standard" diagnostics, as well as user-configurable diagnostics; a Monte-Carlo treatment of collisional processes capable of treating binary and unary collisions and secondary particle generation; and, flexible checkpoint-restart semantics enabling VPIC checkpoint files to be read as input for subsequent simulations. VPIC has a native I/O format that interfaces with the high-performance visualization software Ensight and Paraview. While the common use cases for VPIC employ low-order particles on rectilinear meshes, a framework exists to treat higher-order particles and curvilinear meshes, as well as more advanced field solvers.

Attribution

Researchers who use the VPIC code for scientific research are asked to cite the papers by Kevin Bowers listed below.

  1. Bowers, K. J., B. J. Albright, B. Bergen, L. Yin, K. J. Barker and D. J. Kerbyson, "0.374 Pflop/s Trillion-Particle Kinetic Modeling of Laser Plasma Interaction on Road-runner," Proc. 2008 ACM/IEEE Conf. Supercomputing (Gordon Bell Prize Finalist Paper). http://dl.acm.org/citation.cfm?id=1413435

  2. K.J. Bowers, B.J. Albright, B. Bergen and T.J.T. Kwan, Ultrahigh performance three-dimensional electromagnetic relativistic kinetic plasma simulation, Phys. Plasmas 15, 055703 (2008); http://dx.doi.org/10.1063/1.2840133

  3. K.J. Bowers, B.J. Albright, L. Yin, W. Daughton, V. Roytershteyn, B. Bergen and T.J.T Kwan, Advances in petascale kinetic simulations with VPIC and Roadrunner, Journal of Physics: Conference Series 180, 012055, 2009

Getting the Code

To checkout the VPIC source, do the following:

    git clone https://github.com/lanl/vpic.git

Branches

The stable release of vpic exists on master, the default branch.

For more cutting edge features, consider using the devel branch.

User contributions should target the devel branch.

Requirements

The primary requirement to build VPIC is a C++11 capable compiler and an up-to-date version of MPI.

Build Instructions

    cd vpic 

VPIC uses the CMake build system. To configure a build, do the following from the top-level source directory:

    mkdir build
    cd build

The ./arch directory also contains various cmake scripts (including specific build options) which can help with building, but the user is left to select which compiler they wish to use. The scripts are largely organized into folders by compiler, with specific flags and options set to match the target compiler.

Any of the arch scripts can be invoked specifying the file name from inside a build directory:

    ../arch/reference-Debug

After configuration, simply type:

    make

Three scripts in the ./arch directory are of particular note: lanl-ats1-hsw, lanl-ats1-knl and lanl-cts1. These scripts provide a default way to build VPIC on LANL ATS-1 clusters such as Trinity and Trinitite and LANL CTS-1 clusters. The LANL ATS-1 clusters are the first generation of DOE Advanced Technology Systems and consist of a partition of dual socket Intel Haswell nodes and a partition of single socket Intel Knights Landing nodes. The LANL CTS-1 clusters are the first generation of DOE Commodity Technology Systems and consist of dual socket Intel Broadwell nodes running the TOSS 3.3 operating system. The lanl-ats1-hsw, lanl-ats1-knl and lanl-cts1 scripts are heavily documented and can be configured to provide a large variety of custom builds for their respective platform types. These scripts could also serve as a good starting point for development of a build script for other platform types. Because these scripts also configure the users build environment via the use of module commands, the scripts run both the cmake and make commands.

From the user created build directory, these scripts can be invoked as follows:

    ../arch/lanl-ats1-hsw

or

    ../arch/lanl-ats1-knl

or

    ../arch/lanl-cts1

Advanced users may choose to instead invoke cmake directly and hand select options. Documentation on valid ways to select these options may be found in the lanl-ats1 and lanl-cts1 build scripts mentioned above.

GCC users should ensure the -fno-strict-aliasing compiler flag is set (as shown in ./arch/generic-gcc-sse).

Building an example input deck

After you have successfully built VPIC, you should have an executable in the bin directory called vpic (./bin/vpic). To build an executable from one of the sample input decks (found in ./sample), simply run:

    ./bin/vpic input_deck

where input_deck is the name of your sample deck. For example, to build the harris input deck in the sample subdirectory (assuming that your build directory is located in the top-level source directory):

    ./bin/vpic ../sample/harris

Beginners are advised to read the harris deck thoroughly, as it provides many examples of common uses cases.

Command Line Arguments

Note: Historic VPIC users should note that the format of command line arguments was changed in the first open source release. The equals symbol is no longer accepted, and two dashes are mandatory.

In general, command line arguments take the form --command value, in which two dashes are followed by a keyword, with a space delimiting the command and the value.

The following specific syntax is available to the users:

Threading

Threading (per MPI rank) can be enabled using the following syntax:

    ./binary.Linux --tpp n

Where n specifies the number of threads

Example:

    mpirun -n 2 ./binary.Linux --tpp 2

To run with VPIC with two threads per MPI rank.

Checkpoint Restart

VPIC can restart from a checkpoint dump file, using the following syntax:

    ./binary.Linux --restore <path to file>

Example:

    ./binary.Linux --restore ./restart/restart0 

To restart VPIC using the restart file ./restart/restart0

Compile Time Arguments

Currently, the following options are exposed at compile time for the users consideration:

Particle Array Resizing

  • DISABLE_DYNAMIC_RESIZING (default OFF): Enable to disable the use of dynamic particle resizing
  • SET_MIN_NUM_PARTICLES (default 128 [4kb]): Set the minimum number of particles allowable when dynamically resizing

Threading Model

  • USE_PTHREADS: Use Pthreads for threading model, (default ON)
  • USE_OPENMP: Use OpenMP for threading model

Vectorization

The following CMake variables are used to control the vector implementation that VPIC uses for each SIMD width. Currently, there is support for 128 bit, 256 bit and 512 bit SIMD widths. The default is for each of these CMake variables to be disabled which means that an unvectorized reference implementation of functions will be used.

  • USE_V4_SSE: Enable 4 wide (128-bit) SSE

  • USE_V4_AVX: Enable 4 wide (128-bit) AVX

  • USE_V4_AVX2: Enable 4 wide (128-bit) AVX2

  • USE_V4_ALTIVEC: Enable 4 wide (128-bit) Altivec

  • USE_V4_PORTABLE: Enable 4 wide (128-bit) portable implementation

  • USE_V8_AVX: Enable 8 wide (256-bit) AVX

  • USE_V8_AVX2: Enable 8 wide (256-bit) AVX2

  • USE_V8_PORTABLE: Enable 8 wide (256-bit) portable implementation

  • USE_V16_AVX512: Enable 16 wide (512-bit) AVX512

  • USE_V16_PORTABLE: Enable 16 wide (512-bit) portable implementation

Several functions in VPIC have vector implementations for each of the three SIMD widths. Some only have a single implementation. An example of the latter is move_p which only has a reference implementation and a V4 implementation.

It is possible to have a single CMake vector variable configured as ON for each of the three supported SIMD vector widths. It is recommended to always have a CMake variable configured as ON for the 128 bit SIMD vector width so that move_p will be vectorized. In addition, it is recommended to configure as ON the CMake variable that is associated with the native SIMD vector width of the processor that VPIC is targeting. If a CMake variable is configured as ON for each of the three available SIMD vector widths, then for a given function in VPIC, the implementation which supports the largest SIMD vector length will be chosen. If a V16 implementation exists, it will be chosen. If a V16 implementation does not exist but V8 and V4 implementations exist, the V8 implementation will be chosen. If V16 and V8 implementations do not exist but a V4 implementation does, it will be chosen. If no SIMD vector implementation exists, the unvectorized reference implementation will be chosen.

In summary, when using vector versions on a machine with 256 bit SIMD, the V4 and V8 implementations should be configured as ON. When using a machine with 512 bit SIMD, V4 and V16 implementations should be configured as ON. When choosing a vector implementation for a given SIMD vector length, the implementation that is closest to the SIMD instruction set for the targeted processor should be chosen. The portable versions are most commonly used for debugging the implementation of new intrinsics versions. However, the portable versions are generally more performant than the unvectorized reference implemenation. So, one might consider using the V4_PORTABLE version on ARM processors until a V4_NEON implementation becomes available.

Output

  • VPIC_PRINT_MORE_DIGITS: Enable more digits in timing output of status reports

Particle sorting implementation

The CMake variable below allows building VPIC to use the legacy, thread serial implementation of the particle sort algorithm.

  • USE_LEGACY_SORT: Use legacy thread serial particle sort, (default OFF)

The legacy particle sort implementation is the thread serial particle sort implementation from the legacy v407 version of VPIC. This implementation supports both in-place and out-of-place sorting of the particles. It is very competitive with the thread parallel sort implementation for a small number of threads per MPI rank, i.e. 4 or less, especially on KNL because sorting the particles in-place allows the fraction of particles stored in High Bandwidth Memory (HBM) to remain stored in HBM. Also, the memory footprint of VPIC is reduced by the memory of a particle array which can be significant for particle dominated problems.

The default particle sort implementation is a thread parallel implementation. Currently, it can only perform out-of-place sorting of the particles. It will be more performant than the legacy implementation when using many threads per MPI rank but uses more memory because of the out-of-place sort.

Workflow

Contributors are asked to be aware of the following workflow:

  1. Pull requests are accepted into devel upon tests passing
  2. master should reflect the stable state of the code
  3. Periodic releases will be made from devel into master

Feedback

Feedback, comments, or issues can be raised through GitHub issues.

A mailing list for open collaboration can also be found here

Versioning

Version release summary:

V1.2 (October 2020)

  • Improved Neon intrinsics support
  • Added Takizuka-Abe collision operator
  • Threaded hydro_p pipelines
  • Added unit documentation

V1.1 (March 2019)

  • Added V8 and V16 functionality
  • Improved documentation and build processes
  • Significantly improved testing and correctness capabilities

V1.0

Initial release

Release

This software has been approved for open source release and has been assigned LA-CC-15-109.

Copyright

© (or copyright) 2020. Triad National Security, LLC. All rights reserved. This program was produced under U.S. Government contract 89233218CNA000001 for Los Alamos National Laboratory (LANL), which is operated by Triad National Security, LLC for the U.S. Department of Energy/National Nuclear Security Administration. All rights in the program are reserved by Triad National Security, LLC, and the U.S. Department of Energy/National Nuclear Security Administration. The Government is granted for itself and others acting on its behalf a nonexclusive, paid-up, irrevocable worldwide license in this material to reproduce, prepare derivative works, distribute copies to the public, perform publicly and display publicly, and to permit others to do so.

License

VPIC is distributed under a BSD license.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].