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/opt/serial` | Serial optimized C implementation | 92| `/cpu/self/opt/blocked` | Blocked optimized C implementation | 93| `/cpu/self/tmpl` | Backend template, delegates to `/cpu/self/ref/blocked` | 94| `/cpu/self/ref/memcheck` | Memcheck backend, undefined value checks | 95| `/cpu/self/avx/serial` | Serial AVX implementation | 96| `/cpu/self/avx/blocked` | Blocked AVX implementation | 97| `/cpu/self/xsmm/serial` | Serial LIBXSMM implementation | 98| `/cpu/self/xsmm/blocked` | Blocked LIBXSMM implementation | 99| `/cpu/occa` | Serial OCCA kernels | 100| `/gpu/occa` | CUDA OCCA kernels | 101| `/omp/occa` | OpenMP OCCA kernels | 102| `/ocl/occa` | OpenCL OCCA kernels | 103| `/gpu/cuda/ref` | Reference pure CUDA kernels | 104| `/gpu/cuda/reg` | Pure CUDA kernels using one thread per element | 105| `/gpu/magma` | CUDA MAGMA kernels | 106 107The `/cpu/self/*/serial` backends process one element at a time and are intended for meshes 108with a smaller number of high order elements. The `/cpu/self/*/blocked` backends process 109blocked batches of eight interlaced elements and are intended for meshes with higher numbers 110of elements. 111 112The `/cpu/self/ref/*` backends are written in pure C and provide basic functionality. 113 114The `/cpu/self/opt/*` backends are written in pure C and use partial e-vectors to improve performance. 115 116The `/cpu/self/avx/*` backends rely upon AVX instructions to provide vectorized CPU performance. 117 118The `/cpu/self/xsmm/*` backends rely upon the [LIBXSMM](http://github.com/hfp/libxsmm) package 119to provide vectorized CPU performance. The LIBXSMM backend does not use BLAS or MKL; however, 120if LIBXSMM was linked to MKL, this can be specified with the compilation flag `MKL=1`. 121 122The `/cpu/self/ref/memcheck` backend relies upon the [Valgrind](http://valgrind.org/) Memcheck tool 123to help verify that user QFunctions have no undefined values. To use, run your code with 124Valgrind and the Memcheck backend, e.g. `valgrind ./build/ex1 -ceed /cpu/self/ref/memcheck`. 125 126The `/*/occa` backends rely upon the [OCCA](http://github.com/libocca/occa) package to provide 127cross platform performance. 128 129The `/gpu/cuda/*` backends provide GPU performance strictly using CUDA. 130 131The `/gpu/magma` backend relies upon the [MAGMA](https://bitbucket.org/icl/magma) package. 132 133## Examples 134 135libCEED comes with several examples of its usage, ranging from standalone C 136codes in the `/examples/ceed` directory to examples based on external packages, 137such as MFEM, PETSc, and Nek5000. Nek5000 v18.0 or greater is required. 138 139To build the examples, set the `MFEM_DIR`, `PETSC_DIR` and `NEK5K_DIR` variables 140and run: 141 142```console 143# libCEED examples on CPU and GPU 144cd examples/ceed 145make 146./ex1 -ceed /cpu/self 147./ex1 -ceed /gpu/occa 148cd ../.. 149 150# MFEM+libCEED examples on CPU and GPU 151cd examples/mfem 152make 153./bp1 -ceed /cpu/self -no-vis 154./bp1 -ceed /gpu/occa -no-vis 155cd ../.. 156 157# PETSc+libCEED examples on CPU and GPU 158cd examples/petsc 159make 160./bp1 -ceed /cpu/self 161./bp1 -ceed /gpu/occa 162cd ../.. 163 164cd navier-stokes 165make 166./navierstokes -ceed /cpu/self 167./navierstokes -ceed /gpu/occa 168cd ../.. 169 170# Nek+libCEED examples on CPU and GPU 171cd examples/nek5000 172./make-nek-examples.sh 173./run-nek-example.sh -ceed /cpu/self -b 3 174./run-nek-example.sh -ceed /gpu/occa -b 3 175cd ../.. 176``` 177 178The above code assumes a GPU-capable machine with the OCCA backend 179enabled. Depending on the available backends, other Ceed resource specifiers can 180be provided with the `-ceed` option. 181 182## Benchmarks 183 184A sequence of benchmarks for all enabled backends can be run using 185 186```console 187make benchmarks 188``` 189 190The results from the benchmarks are stored inside the `benchmarks/` directory 191and they can be viewed using the commands (requires python with matplotlib): 192 193```console 194cd benchmarks 195python postprocess-plot.py petsc-bp1-*-output.txt 196python postprocess-plot.py petsc-bp3-*-output.txt 197``` 198 199Using the `benchmarks` target runs a comprehensive set of benchmarks which may 200take some time to run. Subsets of the benchmarks can be run using targets such 201as `make bench-petsc-bp1`, or `make bench-petsc-bp3`. 202 203For more details about the benchmarks, see 204[`benchmarks/README.md`](benchmarks/README.md) 205 206 207## Install 208 209To install libCEED, run 210 211 make install prefix=/usr/local 212 213or (e.g., if creating packages), 214 215 make install prefix=/usr DESTDIR=/packaging/path 216 217Note that along with the library, libCEED installs kernel sources, e.g. OCCA 218kernels are installed in `$prefix/lib/okl`. This allows the OCCA backend to 219build specialized kernels at run-time. In a normal setting, the kernel sources 220will be found automatically (relative to the library file `libceed.so`). 221However, if that fails (e.g. if `libceed.so` is moved), one can copy (cache) the 222kernel sources inside the user OCCA directory, `~/.occa` using 223 224 $(OCCA_DIR)/bin/occa cache ceed $(CEED_DIR)/lib/okl/*.okl 225 226This will allow OCCA to find the sources regardless of the location of the CEED 227library. One may occasionally need to clear the OCCA cache, which can be accomplished 228by removing the `~/.occa` directory or by calling `$(OCCA_DIR)/bin/occa clear -a`. 229 230### pkg-config 231 232In addition to library and header, libCEED provides a [pkg-config][pkg-config1] 233file that can be used to easily compile and link. [For example][pkg-config2], if 234`$prefix` is a standard location or you set the environment variable 235`PKG_CONFIG_PATH`, 236 237 cc `pkg-config --cflags --libs ceed` -o myapp myapp.c 238 239will build `myapp` with libCEED. This can be used with the source or 240installed directories. Most build systems have support for pkg-config. 241 242## Contact 243 244You can reach the libCEED team by emailing [ceed-users@llnl.gov](mailto:ceed-users@llnl.gov) 245or by leaving a comment in the [issue tracker](https://github.com/CEED/libCEED/issues). 246 247## Copyright 248 249The following copyright applies to each file in the CEED software suite, unless 250otherwise stated in the file: 251 252> Copyright (c) 2017, Lawrence Livermore National Security, LLC. Produced at the 253> Lawrence Livermore National Laboratory. LLNL-CODE-734707. All Rights reserved. 254 255See files LICENSE and NOTICE for details. 256 257[ceed-soft]: http://ceed.exascaleproject.org/software/ 258[ecp]: https://exascaleproject.org/exascale-computing-project 259[pkg-config1]: https://en.wikipedia.org/wiki/Pkg-config 260[pkg-config2]: https://people.freedesktop.org/~dbn/pkg-config-guide.html#faq 261
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