1# libCEED: the CEED API Library 2 3[](https://travis-ci.org/CEED/libCEED) 4[](https://codecov.io/gh/CEED/libCEED/) 5[](https://opensource.org/licenses/BSD-2-Clause) 6[](https://codedocs.xyz/CEED/libCEED/) 7 8## Code for Efficient Extensible Discretization 9 10This repository contains an initial low-level API library for the efficient 11high-order discretization methods developed by the ECP co-design [Center for 12Efficient Exascale Discretizations (CEED)](http://ceed.exascaleproject.org). 13While our focus is on high-order finite elements, the approach is mostly 14algebraic and thus applicable to other discretizations in factored form, as 15explained in the API documentation portion of the [Doxygen documentation](https://codedocs.xyz/CEED/libCEED/md_doc_libCEEDapi.html). 16 17One of the challenges with high-order methods is that a global sparse matrix is 18no longer a good representation of a high-order linear operator, both with 19respect to the FLOPs needed for its evaluation, as well as the memory transfer 20needed for a matvec. Thus, high-order methods require a new "format" that still 21represents a linear (or more generally non-linear) operator, but not through a 22sparse matrix. 23 24The goal of libCEED is to propose such a format, as well as supporting 25implementations and data structures, that enable efficient operator evaluation 26on a variety of computational device types (CPUs, GPUs, etc.). This new operator 27description is based on algebraically [factored form](https://codedocs.xyz/CEED/libCEED/md_doc_libCEEDapi.html), 28which is easy to incorporate in a wide variety of applications, without significant 29refactoring of their own discretization infrastructure. 30 31The repository is part of the [CEED software suite][ceed-soft], a collection of 32software benchmarks, miniapps, libraries and APIs for efficient exascale 33discretizations based on high-order finite element and spectral element methods. 34See http://github.com/ceed for more information and source code availability. 35 36The CEED research is supported by the [Exascale Computing Project][ecp] 37(17-SC-20-SC), a collaborative effort of two U.S. Department of Energy 38organizations (Office of Science and the National Nuclear Security 39Administration) responsible for the planning and preparation of a [capable 40exascale ecosystem](https://exascaleproject.org/what-is-exascale), including 41software, applications, hardware, advanced system engineering and early testbed 42platforms, in support of the nation’s exascale computing imperative. 43 44For more details on the CEED API see http://ceed.exascaleproject.org/ceed-code/. 45 46## Building 47 48The CEED library, `libceed`, is a C99 library with no external dependencies. It 49can be built using 50 51 make 52 53or, with optimization flags 54 55 make OPT='-O3 -march=skylake-avx512 -ffp-contract=fast' 56 57These optimization flags are used by all languages (C, C++, Fortran) and this 58makefile variable can also be set for testing and examples (below). 59 60The library attempts to automatically detect support for the AVX 61instruction set using gcc-style compiler options for the host. 62Support may need to be manually specified via 63 64 make AVX=1 65 66or 67 68 make AVX=0 69 70if your compiler does not support gcc-style options, if you are cross 71compiling, etc. 72 73## Testing 74 75The test suite produces [TAP](https://testanything.org) output and is run by: 76 77 make test 78 79or, using the `prove` tool distributed with Perl (recommended) 80 81 make prove 82 83## Backends 84 85There are multiple supported backends, which can be selected at runtime in the examples: 86 87| CEED resource | Backend | 88| :----------------------- | :------------------------------------------------ | 89| `/cpu/self/ref/serial` | Serial reference implementation | 90| `/cpu/self/ref/blocked` | Blocked refrence implementation | 91| `/cpu/self/ref/memcheck` | Memcheck backend, undefined value checks | 92| `/cpu/self/opt/serial` | Serial optimized C implementation | 93| `/cpu/self/opt/blocked` | Blocked optimized C implementation | 94| `/cpu/self/avx/serial` | Serial AVX implementation | 95| `/cpu/self/avx/blocked` | Blocked AVX implementation | 96| `/cpu/self/xsmm/serial` | Serial LIBXSMM implementation | 97| `/cpu/self/xsmm/blocked` | Blocked LIBXSMM implementation | 98| `/cpu/occa` | Serial OCCA kernels | 99| `/gpu/occa` | CUDA OCCA kernels | 100| `/omp/occa` | OpenMP OCCA kernels | 101| `/ocl/occa` | OpenCL OCCA kernels | 102| `/gpu/cuda/ref` | Reference pure CUDA kernels | 103| `/gpu/cuda/reg` | Pure CUDA kernels using one thread per element | 104| `/gpu/cuda/shared` | Optimized pure CUDA kernels using shared memory | 105| `/gpu/cuda/gen` | Optimized pure CUDA kernels using code generation | 106| `/gpu/magma` | CUDA MAGMA kernels | 107 108The `/cpu/self/*/serial` backends process one element at a time and are intended for meshes 109with a smaller number of high order elements. The `/cpu/self/*/blocked` backends process 110blocked batches of eight interlaced elements and are intended for meshes with higher numbers 111of elements. 112 113The `/cpu/self/ref/*` backends are written in pure C and provide basic functionality. 114 115The `/cpu/self/opt/*` backends are written in pure C and use partial e-vectors to improve performance. 116 117The `/cpu/self/avx/*` backends rely upon AVX instructions to provide vectorized CPU performance. 118 119The `/cpu/self/xsmm/*` backends rely upon the [LIBXSMM](http://github.com/hfp/libxsmm) package 120to provide vectorized CPU performance. If linking MKL and LIBXSMM is desired but 121the Makefile is not detecting `MKLROOT`, linking libCEED against MKL can be 122forced by setting the environment variable `MKL=1`. 123 124The `/cpu/self/ref/memcheck` backend relies upon the [Valgrind](http://valgrind.org/) Memcheck tool 125to help verify that user QFunctions have no undefined values. To use, run your code with 126Valgrind and the Memcheck backend, e.g. `valgrind ./build/ex1 -ceed /cpu/self/ref/memcheck`. A 127'development' or 'debugging' version of Valgrind with headers is required to use this backend. 128 129The `/*/occa` backends rely upon the [OCCA](http://github.com/libocca/occa) package to provide 130cross platform performance. 131 132The `/gpu/cuda/*` backends provide GPU performance strictly using CUDA. 133 134The `/gpu/magma` backend relies upon the [MAGMA](https://bitbucket.org/icl/magma) package. 135 136## Examples 137 138libCEED comes with several examples of its usage, ranging from standalone C 139codes in the `/examples/ceed` directory to examples based on external packages, 140such as MFEM, PETSc, and Nek5000. Nek5000 v18.0 or greater is required. 141 142To build the examples, set the `MFEM_DIR`, `PETSC_DIR` and `NEK5K_DIR` variables 143and run: 144 145```console 146# libCEED examples on CPU and GPU 147cd examples/ceed 148make 149./ex1 -ceed /cpu/self 150./ex1 -ceed /gpu/occa 151cd ../.. 152 153# MFEM+libCEED examples on CPU and GPU 154cd examples/mfem 155make 156./bp1 -ceed /cpu/self -no-vis 157./bp3 -ceed /gpu/occa -no-vis 158cd ../.. 159 160# Nek5000+libCEED examples on CPU and GPU 161cd examples/nek 162make 163./nek-examples.sh -e bp1 -ceed /cpu/self -b 3 164./nek-examples.sh -e bp3 -ceed /gpu/occa -b 3 165cd ../.. 166 167# PETSc+libCEED examples on CPU and GPU 168cd examples/petsc 169make 170./bps -problem bp1 -ceed /cpu/self 171./bps -problem bp2 -ceed /gpu/occa 172./bps -problem bp3 -ceed /cpu/self 173./bps -problem bp4 -ceed /gpu/occa 174./bps -problem bp5 -ceed /cpu/self 175./bps -problem bp6 -ceed /gpu/occa 176cd ../.. 177 178cd examples/navier-stokes 179make 180./navierstokes -ceed /cpu/self 181./navierstokes -ceed /gpu/occa 182cd ../.. 183``` 184 185The above code assumes a GPU-capable machine with the OCCA backend 186enabled. Depending on the available backends, other Ceed resource specifiers can 187be provided with the `-ceed` option. 188 189## Benchmarks 190 191A sequence of benchmarks for all enabled backends can be run using 192 193```console 194make benchmarks 195``` 196 197The results from the benchmarks are stored inside the `benchmarks/` directory 198and they can be viewed using the commands (requires python with matplotlib): 199 200```console 201cd benchmarks 202python postprocess-plot.py petsc-bps-bp1-*-output.txt 203python postprocess-plot.py petsc-bps-bp3-*-output.txt 204``` 205 206Using the `benchmarks` target runs a comprehensive set of benchmarks which may 207take some time to run. Subsets of the benchmarks can be run using the scripts in the `benchmarks` folder. 208 209For more details about the benchmarks, see 210[`benchmarks/README.md`](benchmarks/README.md) 211 212 213## Install 214 215To install libCEED, run 216 217 make install prefix=/usr/local 218 219or (e.g., if creating packages), 220 221 make install prefix=/usr DESTDIR=/packaging/path 222 223Note that along with the library, libCEED installs kernel sources, e.g. OCCA 224kernels are installed in `$prefix/lib/okl`. This allows the OCCA backend to 225build specialized kernels at run-time. In a normal setting, the kernel sources 226will be found automatically (relative to the library file `libceed.so`). 227However, if that fails (e.g. if `libceed.so` is moved), one can copy (cache) the 228kernel sources inside the user OCCA directory, `~/.occa` using 229 230 $(OCCA_DIR)/bin/occa cache ceed $(CEED_DIR)/lib/okl/*.okl 231 232This will allow OCCA to find the sources regardless of the location of the CEED 233library. One may occasionally need to clear the OCCA cache, which can be accomplished 234by removing the `~/.occa` directory or by calling `$(OCCA_DIR)/bin/occa clear -a`. 235 236### pkg-config 237 238In addition to library and header, libCEED provides a [pkg-config][pkg-config1] 239file that can be used to easily compile and link. [For example][pkg-config2], if 240`$prefix` is a standard location or you set the environment variable 241`PKG_CONFIG_PATH`, 242 243 cc `pkg-config --cflags --libs ceed` -o myapp myapp.c 244 245will build `myapp` with libCEED. This can be used with the source or 246installed directories. Most build systems have support for pkg-config. 247 248## Contact 249 250You can reach the libCEED team by emailing [ceed-users@llnl.gov](mailto:ceed-users@llnl.gov) 251or by leaving a comment in the [issue tracker](https://github.com/CEED/libCEED/issues). 252 253## Copyright 254 255The following copyright applies to each file in the CEED software suite, unless 256otherwise stated in the file: 257 258> Copyright (c) 2017, Lawrence Livermore National Security, LLC. Produced at the 259> Lawrence Livermore National Laboratory. LLNL-CODE-734707. All Rights reserved. 260 261See files LICENSE and NOTICE for details. 262 263[ceed-soft]: http://ceed.exascaleproject.org/software/ 264[ecp]: https://exascaleproject.org/exascale-computing-project 265[pkg-config1]: https://en.wikipedia.org/wiki/Pkg-config 266[pkg-config2]: https://people.freedesktop.org/~dbn/pkg-config-guide.html#faq 267
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