1# libCEED: Efficient Extensible Discretization 2 3[![GitHub Actions][github-badge]][github-link] 4[![GitLab-CI][gitlab-badge]][gitlab-link] 5[![Code coverage][codecov-badge]][codecov-link] 6[![BSD-2-Clause][license-badge]][license-link] 7[![Documentation][doc-badge]][doc-link] 8[![JOSS paper][joss-badge]][joss-link] 9[![Binder][binder-badge]][binder-link] 10 11## Summary and Purpose 12 13libCEED provides fast algebra for element-based discretizations, designed for performance portability, run-time flexibility, and clean embedding in higher level libraries and applications. 14It offers a C99 interface as well as bindings for Fortran, Python, Julia, and Rust. 15While our focus is on high-order finite elements, the approach is mostly algebraic and thus applicable to other discretizations in factored form, as explained in the [user manual](https://libceed.org/en/latest/) and API implementation portion of the [documentation](https://libceed.org/en/latest/api/). 16 17One of the challenges with high-order methods is that a global sparse matrix is no longer a good representation of a high-order linear operator, both with respect to the FLOPs needed for its evaluation, as well as the memory transfer needed for a matvec. 18Thus, high-order methods require a new "format" that still represents a linear (or more generally non-linear) operator, but not through a sparse matrix. 19 20The goal of libCEED is to propose such a format, as well as supporting implementations and data structures, that enable efficient operator evaluation on a variety of computational device types (CPUs, GPUs, etc.). 21This new operator description is based on algebraically [factored form](https://libceed.org/en/latest/libCEEDapi/#finite-element-operator-decomposition), which is easy to incorporate in a wide variety of applications, without significant refactoring of their own discretization infrastructure. 22 23The repository is part of the [CEED software suite](http://ceed.exascaleproject.org/software/), a collection of software benchmarks, miniapps, libraries and APIs for efficient exascale discretizations based on high-order finite element and spectral element methods. 24See <http://github.com/ceed> for more information and source code availability. 25 26The CEED research is supported by the [Exascale Computing Project](https://exascaleproject.org/exascale-computing-project) (17-SC-20-SC), a collaborative effort of two U.S. Department of Energy organizations (Office of Science and the National Nuclear Security Administration) responsible for the planning and preparation of a [capable exascale ecosystem](https://exascaleproject.org/what-is-exascale), including software, applications, hardware, advanced system engineering and early testbed platforms, in support of the nation’s exascale computing imperative. 27 28For more details on the CEED API see the [user manual](https://libceed.org/en/latest/). 29 30% gettingstarted-inclusion-marker 31 32## Building 33 34The CEED library, `libceed`, is a C99 library with no required dependencies, and with Fortran, Python, Julia, and Rust interfaces. 35It can be built using: 36 37```console 38$ make 39``` 40 41or, with optimization flags: 42 43```console 44$ make OPT='-O3 -march=skylake-avx512 -ffp-contract=fast' 45``` 46 47These optimization flags are used by all languages (C, C++, Fortran) and this makefile variable can also be set for testing and examples (below). 48 49The library attempts to automatically detect support for the AVX instruction set using gcc-style compiler options for the host. 50Support may need to be manually specified via: 51 52```console 53$ make AVX=1 54``` 55 56or: 57 58```console 59$ make AVX=0 60``` 61 62if your compiler does not support gcc-style options, if you are cross compiling, etc. 63 64To enable CUDA support, add `CUDA_DIR=/opt/cuda` or an appropriate directory to your `make` invocation. 65To enable HIP support, add `ROCM_DIR=/opt/rocm` or an appropriate directory. 66To enable SYCL support, add `SYCL_DIR=/opt/sycl` or an appropriate directory. 67Note that SYCL backends require building with oneAPI compilers as well: 68 69```console 70$ . /opt/intel/oneapi/setvars.sh 71$ make SYCL_DIR=/opt/intel/oneapi/compiler/latest/linux SYCLCXX=icpx CC=icx CXX=icpx 72``` 73 74The library can be configured for host applications which use OpenMP paralellism via: 75 76```console 77$ make OPENMP=1 78``` 79 80which will allow operators created and applied from different threads inside an `omp parallel` region. 81 82To store these or other arguments as defaults for future invocations of `make`, use: 83 84```console 85$ make configure CUDA_DIR=/usr/local/cuda ROCM_DIR=/opt/rocm OPT='-O3 -march=znver2' 86``` 87 88which stores these variables in `config.mk`. 89 90### WebAssembly 91 92libCEED can be built for WASM using [Emscripten](https://emscripten.org). For example, one can build the library and run a standalone WASM executable using 93 94``` console 95$ emmake make build/ex2-surface.wasm 96$ wasmer build/ex2-surface.wasm -- -s 200000 97``` 98 99## Additional Language Interfaces 100 101The Fortran interface is built alongside the library automatically. 102 103Python users can install using: 104 105```console 106$ pip install libceed 107``` 108 109or in a clone of the repository via `pip install .`. 110 111Julia users can install using: 112 113```console 114$ julia 115julia> ] 116pkg> add LibCEED 117``` 118 119See the [LibCEED.jl documentation](http://ceed.exascaleproject.org/libCEED-julia-docs/dev/) for more information. 120 121Rust users can include libCEED via `Cargo.toml`: 122 123```toml 124[dependencies] 125libceed = "0.12.0" 126``` 127 128See the [Cargo documentation](https://doc.rust-lang.org/cargo/reference/specifying-dependencies.html#specifying-dependencies-from-git-repositories) for details. 129 130## Testing 131 132The test suite produces [TAP](https://testanything.org) output and is run by: 133 134```console 135$ make test 136``` 137 138or, using the `prove` tool distributed with Perl (recommended): 139 140```console 141$ make prove 142``` 143 144## Backends 145 146There are multiple supported backends, which can be selected at runtime in the examples: 147 148| CEED resource | Backend | Deterministic Capable | 149| :--- | :--- | :---: | 150|| 151| **CPU Native** | 152| `/cpu/self/ref/serial` | Serial reference implementation | Yes | 153| `/cpu/self/ref/blocked` | Blocked reference implementation | Yes | 154| `/cpu/self/opt/serial` | Serial optimized C implementation | Yes | 155| `/cpu/self/opt/blocked` | Blocked optimized C implementation | Yes | 156| `/cpu/self/avx/serial` | Serial AVX implementation | Yes | 157| `/cpu/self/avx/blocked` | Blocked AVX implementation | Yes | 158|| 159| **CPU Valgrind** | 160| `/cpu/self/memcheck/*` | Memcheck backends, undefined value checks | Yes | 161|| 162| **CPU LIBXSMM** | 163| `/cpu/self/xsmm/serial` | Serial LIBXSMM implementation | Yes | 164| `/cpu/self/xsmm/blocked` | Blocked LIBXSMM implementation | Yes | 165|| 166| **CUDA Native** | 167| `/gpu/cuda/ref` | Reference pure CUDA kernels | Yes | 168| `/gpu/cuda/shared` | Optimized pure CUDA kernels using shared memory | Yes | 169| `/gpu/cuda/gen` | Optimized pure CUDA kernels using code generation | No | 170|| 171| **HIP Native** | 172| `/gpu/hip/ref` | Reference pure HIP kernels | Yes | 173| `/gpu/hip/shared` | Optimized pure HIP kernels using shared memory | Yes | 174| `/gpu/hip/gen` | Optimized pure HIP kernels using code generation | No | 175|| 176| **SYCL Native** | 177| `/gpu/sycl/ref` | Reference pure SYCL kernels | Yes | 178| `/gpu/sycl/shared` | Optimized pure SYCL kernels using shared memory | Yes | 179|| 180| **MAGMA** | 181| `/gpu/cuda/magma` | CUDA MAGMA kernels | No | 182| `/gpu/cuda/magma/det` | CUDA MAGMA kernels | Yes | 183| `/gpu/hip/magma` | HIP MAGMA kernels | No | 184| `/gpu/hip/magma/det` | HIP MAGMA kernels | Yes | 185|| 186| **OCCA** | 187| `/*/occa` | Selects backend based on available OCCA modes | Yes | 188| `/cpu/self/occa` | OCCA backend with serial CPU kernels | Yes | 189| `/cpu/openmp/occa` | OCCA backend with OpenMP kernels | Yes | 190| `/cpu/dpcpp/occa` | OCCA backend with DPC++ kernels | Yes | 191| `/gpu/cuda/occa` | OCCA backend with CUDA kernels | Yes | 192| `/gpu/hip/occa` | OCCA backend with HIP kernels | Yes | 193 194The `/cpu/self/*/serial` backends process one element at a time and are intended for meshes with a smaller number of high order elements. 195The `/cpu/self/*/blocked` backends process blocked batches of eight interlaced elements and are intended for meshes with higher numbers of elements. 196 197The `/cpu/self/ref/*` backends are written in pure C and provide basic functionality. 198 199The `/cpu/self/opt/*` backends are written in pure C and use partial e-vectors to improve performance. 200 201The `/cpu/self/avx/*` backends rely upon AVX instructions to provide vectorized CPU performance. 202 203The `/cpu/self/memcheck/*` backends rely upon the [Valgrind](https://valgrind.org/) Memcheck tool to help verify that user QFunctions have no undefined values. 204To use, run your code with Valgrind and the Memcheck backends, e.g. `valgrind ./build/ex1 -ceed /cpu/self/ref/memcheck`. 205A 'development' or 'debugging' version of Valgrind with headers is required to use this backend. 206This backend can be run in serial or blocked mode and defaults to running in the serial mode if `/cpu/self/memcheck` is selected at runtime. 207 208The `/cpu/self/xsmm/*` backends rely upon the [LIBXSMM](https://github.com/libxsmm/libxsmm) package to provide vectorized CPU performance. 209If linking MKL and LIBXSMM is desired but the Makefile is not detecting `MKLROOT`, linking libCEED against MKL can be forced by setting the environment variable `MKL=1`. 210The LIBXSMM `main` development branch from 7 April 2024 or newer is required. 211 212The `/gpu/cuda/*` backends provide GPU performance strictly using CUDA. 213 214The `/gpu/hip/*` backends provide GPU performance strictly using HIP. 215They are based on the `/gpu/cuda/*` backends. 216ROCm version 4.2 or newer is required. 217 218The `/gpu/sycl/*` backends provide GPU performance strictly using SYCL. 219They are based on the `/gpu/cuda/*` and `/gpu/hip/*` backends. 220 221The `/gpu/*/magma/*` backends rely upon the [MAGMA](https://bitbucket.org/icl/magma) package. 222To enable the MAGMA backends, the environment variable `MAGMA_DIR` must point to the top-level MAGMA directory, with the MAGMA library located in `$(MAGMA_DIR)/lib/`. 223By default, `MAGMA_DIR` is set to `../magma`; to build the MAGMA backends with a MAGMA installation located elsewhere, create a link to `magma/` in libCEED's parent directory, or set `MAGMA_DIR` to the proper location. 224MAGMA version 2.5.0 or newer is required. 225Currently, each MAGMA library installation is only built for either CUDA or HIP. 226The corresponding set of libCEED backends (`/gpu/cuda/magma/*` or `/gpu/hip/magma/*`) will automatically be built for the version of the MAGMA library found in `MAGMA_DIR`. 227 228Users can specify a device for all CUDA, HIP, and MAGMA backends through adding `:device_id=#` after the resource name. 229For example: 230 231> - `/gpu/cuda/gen:device_id=1` 232 233The `/*/occa` backends rely upon the [OCCA](http://github.com/libocca/occa) package to provide cross platform performance. 234To enable the OCCA backend, the environment variable `OCCA_DIR` must point to the top-level OCCA directory, with the OCCA library located in the `${OCCA_DIR}/lib` (By default, `OCCA_DIR` is set to `../occa`). 235OCCA version 1.4.0 or newer is required. 236 237Users can pass specific OCCA device properties after setting the CEED resource. 238For example: 239 240> - `"/*/occa:mode='CUDA',device_id=0"` 241 242Bit-for-bit reproducibility is important in some applications. 243However, some libCEED backends use non-deterministic operations, such as `atomicAdd` for increased performance. 244The backends which are capable of generating reproducible results, with the proper compilation options, are highlighted in the list above. 245 246## Examples 247 248libCEED comes with several examples of its usage, ranging from standalone C codes in the `/examples/ceed` directory to examples based on external packages, such as MFEM, PETSc, and Nek5000. 249Nek5000 v18.0 or greater is required. 250 251To build the examples, set the `MFEM_DIR`, `PETSC_DIR`, and `NEK5K_DIR` variables and run: 252 253```console 254$ cd examples/ 255``` 256 257% running-examples-inclusion-marker 258 259```console 260# libCEED examples on CPU and GPU 261$ cd ceed/ 262$ make 263$ ./ex1-volume -ceed /cpu/self 264$ ./ex1-volume -ceed /gpu/cuda 265$ ./ex2-surface -ceed /cpu/self 266$ ./ex2-surface -ceed /gpu/cuda 267$ cd .. 268 269# MFEM+libCEED examples on CPU and GPU 270$ cd mfem/ 271$ make 272$ ./bp1 -ceed /cpu/self -no-vis 273$ ./bp3 -ceed /gpu/cuda -no-vis 274$ cd .. 275 276# Nek5000+libCEED examples on CPU and GPU 277$ cd nek/ 278$ make 279$ ./nek-examples.sh -e bp1 -ceed /cpu/self -b 3 280$ ./nek-examples.sh -e bp3 -ceed /gpu/cuda -b 3 281$ cd .. 282 283# PETSc+libCEED examples on CPU and GPU 284$ cd petsc/ 285$ make 286$ ./bps -problem bp1 -ceed /cpu/self 287$ ./bps -problem bp2 -ceed /gpu/cuda 288$ ./bps -problem bp3 -ceed /cpu/self 289$ ./bps -problem bp4 -ceed /gpu/cuda 290$ ./bps -problem bp5 -ceed /cpu/self 291$ ./bps -problem bp6 -ceed /gpu/cuda 292$ cd .. 293 294$ cd petsc/ 295$ make 296$ ./bpsraw -problem bp1 -ceed /cpu/self 297$ ./bpsraw -problem bp2 -ceed /gpu/cuda 298$ ./bpsraw -problem bp3 -ceed /cpu/self 299$ ./bpsraw -problem bp4 -ceed /gpu/cuda 300$ ./bpsraw -problem bp5 -ceed /cpu/self 301$ ./bpsraw -problem bp6 -ceed /gpu/cuda 302$ cd .. 303 304$ cd petsc/ 305$ make 306$ ./bpssphere -problem bp1 -ceed /cpu/self 307$ ./bpssphere -problem bp2 -ceed /gpu/cuda 308$ ./bpssphere -problem bp3 -ceed /cpu/self 309$ ./bpssphere -problem bp4 -ceed /gpu/cuda 310$ ./bpssphere -problem bp5 -ceed /cpu/self 311$ ./bpssphere -problem bp6 -ceed /gpu/cuda 312$ cd .. 313 314$ cd petsc/ 315$ make 316$ ./area -problem cube -ceed /cpu/self -degree 3 317$ ./area -problem cube -ceed /gpu/cuda -degree 3 318$ ./area -problem sphere -ceed /cpu/self -degree 3 -dm_refine 2 319$ ./area -problem sphere -ceed /gpu/cuda -degree 3 -dm_refine 2 320 321$ cd fluids/ 322$ make 323$ ./navierstokes -ceed /cpu/self -degree 1 324$ ./navierstokes -ceed /gpu/cuda -degree 1 325$ cd .. 326 327$ cd solids/ 328$ make 329$ ./elasticity -ceed /cpu/self -mesh [.exo file] -degree 2 -E 1 -nu 0.3 -problem Linear -forcing mms 330$ ./elasticity -ceed /gpu/cuda -mesh [.exo file] -degree 2 -E 1 -nu 0.3 -problem Linear -forcing mms 331$ cd .. 332``` 333 334For the last example shown, sample meshes to be used in place of `[.exo file]` can be found at <https://github.com/jeremylt/ceedSampleMeshes> 335 336The above code assumes a GPU-capable machine with the CUDA backends enabled. 337Depending on the available backends, other CEED resource specifiers can be provided with the `-ceed` option. 338Other command line arguments can be found in [examples/petsc](https://github.com/CEED/libCEED/blob/main/examples/petsc/README.md). 339 340% benchmarks-marker 341 342## Benchmarks 343 344A sequence of benchmarks for all enabled backends can be run using: 345 346```console 347$ make benchmarks 348``` 349 350The results from the benchmarks are stored inside the `benchmarks/` directory and they can be viewed using the commands (requires python with matplotlib): 351 352```console 353$ cd benchmarks 354$ python postprocess-plot.py petsc-bps-bp1-*-output.txt 355$ python postprocess-plot.py petsc-bps-bp3-*-output.txt 356``` 357 358Using the `benchmarks` target runs a comprehensive set of benchmarks which may take some time to run. 359Subsets of the benchmarks can be run using the scripts in the `benchmarks` folder. 360 361For more details about the benchmarks, see the `benchmarks/README.md` file. 362 363## Install 364 365To install libCEED, run: 366 367```console 368$ make install prefix=/path/to/install/dir 369``` 370 371or (e.g., if creating packages): 372 373```console 374$ make install prefix=/usr DESTDIR=/packaging/path 375``` 376 377To build and install in separate steps, run: 378 379```console 380$ make for_install=1 prefix=/path/to/install/dir 381$ make install prefix=/path/to/install/dir 382``` 383 384The usual variables like `CC` and `CFLAGS` are used, and optimization flags for all languages can be set using the likes of `OPT='-O3 -march=native'`. 385Use `STATIC=1` to build static libraries (`libceed.a`). 386 387To install libCEED for Python, run: 388 389```console 390$ pip install libceed 391``` 392 393with the desired setuptools options, such as `--user`. 394 395### pkg-config 396 397In addition to library and header, libCEED provides a [pkg-config](https://en.wikipedia.org/wiki/Pkg-config) file that can be used to easily compile and link. 398[For example](https://people.freedesktop.org/~dbn/pkg-config-guide.html#faq), if `$prefix` is a standard location or you set the environment variable `PKG_CONFIG_PATH`: 399 400```console 401$ cc `pkg-config --cflags --libs ceed` -o myapp myapp.c 402``` 403 404will build `myapp` with libCEED. 405This can be used with the source or installed directories. 406Most build systems have support for pkg-config. 407 408## Contact 409 410You can reach the libCEED team by emailing [ceed-users@llnl.gov](mailto:ceed-users@llnl.gov) or by leaving a comment in the [issue tracker](https://github.com/CEED/libCEED/issues). 411 412## How to Cite 413 414If you utilize libCEED please cite: 415 416```bibtex 417@article{libceed-joss-paper, 418 author = {Jed Brown and Ahmad Abdelfattah and Valeria Barra and Natalie Beams and Jean Sylvain Camier and Veselin Dobrev and Yohann Dudouit and Leila Ghaffari and Tzanio Kolev and David Medina and Will Pazner and Thilina Ratnayaka and Jeremy Thompson and Stan Tomov}, 419 title = {{libCEED}: Fast algebra for high-order element-based discretizations}, 420 journal = {Journal of Open Source Software}, 421 year = {2021}, 422 publisher = {The Open Journal}, 423 volume = {6}, 424 number = {63}, 425 pages = {2945}, 426 doi = {10.21105/joss.02945} 427} 428``` 429 430The archival copy of the libCEED user manual is maintained on [Zenodo](https://doi.org/10.5281/zenodo.4302736). 431To cite the user manual: 432 433```bibtex 434@misc{libceed-user-manual, 435 author = {Abdelfattah, Ahmad and 436 Barra, Valeria and 437 Beams, Natalie and 438 Brown, Jed and 439 Camier, Jean-Sylvain and 440 Dobrev, Veselin and 441 Dudouit, Yohann and 442 Ghaffari, Leila and 443 Grimberg, Sebastian and 444 Kolev, Tzanio and 445 Medina, David and 446 Pazner, Will and 447 Ratnayaka, Thilina and 448 Shakeri, Rezgar and 449 Thompson, Jeremy L and 450 Tomov, Stanimire and 451 Wright III, James}, 452 title = {{libCEED} User Manual}, 453 month = nov, 454 year = 2023, 455 publisher = {Zenodo}, 456 version = {0.12.0}, 457 doi = {10.5281/zenodo.10062388} 458} 459``` 460 461For libCEED's Python interface please cite: 462 463```bibtex 464@InProceedings{libceed-paper-proc-scipy-2020, 465 author = {{V}aleria {B}arra and {J}ed {B}rown and {J}eremy {T}hompson and {Y}ohann {D}udouit}, 466 title = {{H}igh-performance operator evaluations with ease of use: lib{C}{E}{E}{D}'s {P}ython interface}, 467 booktitle = {{P}roceedings of the 19th {P}ython in {S}cience {C}onference}, 468 pages = {85 - 90}, 469 year = {2020}, 470 editor = {{M}eghann {A}garwal and {C}hris {C}alloway and {D}illon {N}iederhut and {D}avid {S}hupe}, 471 doi = {10.25080/Majora-342d178e-00c} 472} 473``` 474 475The BibTeX entries for these references can be found in the `doc/bib/references.bib` file. 476 477## Copyright 478 479The following copyright applies to each file in the CEED software suite, unless otherwise stated in the file: 480 481> Copyright (c) 2017-2024, Lawrence Livermore National Security, LLC and other CEED contributors. 482> All rights reserved. 483 484See files LICENSE and NOTICE for details. 485 486[github-badge]: https://github.com/CEED/libCEED/workflows/C/Fortran/badge.svg 487[github-link]: https://github.com/CEED/libCEED/actions 488[gitlab-badge]: https://gitlab.com/libceed/libCEED/badges/main/pipeline.svg?key_text=GitLab-CI 489[gitlab-link]: https://gitlab.com/libceed/libCEED/-/pipelines?page=1&scope=all&ref=main 490[codecov-badge]: https://codecov.io/gh/CEED/libCEED/branch/main/graphs/badge.svg 491[codecov-link]: https://codecov.io/gh/CEED/libCEED/ 492[license-badge]: https://img.shields.io/badge/License-BSD%202--Clause-orange.svg 493[license-link]: https://opensource.org/licenses/BSD-2-Clause 494[doc-badge]: https://readthedocs.org/projects/libceed/badge/?version=latest 495[doc-link]: https://libceed.org/en/latest/?badge=latest 496[joss-badge]: https://joss.theoj.org/papers/10.21105/joss.02945/status.svg 497[joss-link]: https://doi.org/10.21105/joss.02945 498[binder-badge]: http://mybinder.org/badge_logo.svg 499[binder-link]: https://mybinder.org/v2/gh/CEED/libCEED/main?urlpath=lab/tree/examples/python/tutorial-0-ceed.ipynb 500
