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. The LIBXSMM backend does not use BLAS or MKL; however, 121if LIBXSMM was linked to MKL, this can be specified with the compilation flag `MKL=1`. 122 123The `/cpu/self/ref/memcheck` backend relies upon the [Valgrind](http://valgrind.org/) Memcheck tool 124to help verify that user QFunctions have no undefined values. To use, run your code with 125Valgrind and the Memcheck backend, e.g. `valgrind ./build/ex1 -ceed /cpu/self/ref/memcheck`. A 126'development' or 'debugging' version of Valgrind with headers is required to use this backend. 127 128The `/*/occa` backends rely upon the [OCCA](http://github.com/libocca/occa) package to provide 129cross platform performance. 130 131The `/gpu/cuda/*` backends provide GPU performance strictly using CUDA. 132 133The `/gpu/magma` backend relies upon the [MAGMA](https://bitbucket.org/icl/magma) package. 134 135## Examples 136 137libCEED comes with several examples of its usage, ranging from standalone C 138codes in the `/examples/ceed` directory to examples based on external packages, 139such as MFEM, PETSc, and Nek5000. Nek5000 v18.0 or greater is required. 140 141To build the examples, set the `MFEM_DIR`, `PETSC_DIR` and `NEK5K_DIR` variables 142and run: 143 144```console 145# libCEED examples on CPU and GPU 146cd examples/ceed 147make 148./ex1 -ceed /cpu/self 149./ex1 -ceed /gpu/occa 150cd ../.. 151 152# MFEM+libCEED examples on CPU and GPU 153cd examples/mfem 154make 155./bp1 -ceed /cpu/self -no-vis 156./bp3 -ceed /gpu/occa -no-vis 157cd ../.. 158 159# Nek5000+libCEED examples on CPU and GPU 160cd examples/nek 161make 162./nek-examples.sh -e bp1 -ceed /cpu/self -b 3 163./nek-examples.sh -e bp3 -ceed /gpu/occa -b 3 164cd ../.. 165 166# PETSc+libCEED examples on CPU and GPU 167cd examples/petsc 168make 169./bps -problem bp1 -ceed /cpu/self 170./bps -problem bp2 -ceed /gpu/occa 171./bps -problem bp3 -ceed /cpu/self 172./bps -problem bp4 -ceed /gpu/occa 173./bps -problem bp5 -ceed /cpu/self 174./bps -problem bp6 -ceed /gpu/occa 175cd ../.. 176 177cd examples/navier-stokes 178make 179./navierstokes -ceed /cpu/self 180./navierstokes -ceed /gpu/occa 181cd ../.. 182``` 183 184The above code assumes a GPU-capable machine with the OCCA backend 185enabled. Depending on the available backends, other Ceed resource specifiers can 186be provided with the `-ceed` option. 187 188## Benchmarks 189 190A sequence of benchmarks for all enabled backends can be run using 191 192```console 193make benchmarks 194``` 195 196The results from the benchmarks are stored inside the `benchmarks/` directory 197and they can be viewed using the commands (requires python with matplotlib): 198 199```console 200cd benchmarks 201python postprocess-plot.py petsc-bps-bp1-*-output.txt 202python postprocess-plot.py petsc-bps-bp3-*-output.txt 203``` 204 205Using the `benchmarks` target runs a comprehensive set of benchmarks which may 206take some time to run. Subsets of the benchmarks can be run using the scripts in the `benchmarks` folder. 207 208For more details about the benchmarks, see 209[`benchmarks/README.md`](benchmarks/README.md) 210 211 212## Install 213 214To install libCEED, run 215 216 make install prefix=/usr/local 217 218or (e.g., if creating packages), 219 220 make install prefix=/usr DESTDIR=/packaging/path 221 222Note that along with the library, libCEED installs kernel sources, e.g. OCCA 223kernels are installed in `$prefix/lib/okl`. This allows the OCCA backend to 224build specialized kernels at run-time. In a normal setting, the kernel sources 225will be found automatically (relative to the library file `libceed.so`). 226However, if that fails (e.g. if `libceed.so` is moved), one can copy (cache) the 227kernel sources inside the user OCCA directory, `~/.occa` using 228 229 $(OCCA_DIR)/bin/occa cache ceed $(CEED_DIR)/lib/okl/*.okl 230 231This will allow OCCA to find the sources regardless of the location of the CEED 232library. One may occasionally need to clear the OCCA cache, which can be accomplished 233by removing the `~/.occa` directory or by calling `$(OCCA_DIR)/bin/occa clear -a`. 234 235### pkg-config 236 237In addition to library and header, libCEED provides a [pkg-config][pkg-config1] 238file that can be used to easily compile and link. [For example][pkg-config2], if 239`$prefix` is a standard location or you set the environment variable 240`PKG_CONFIG_PATH`, 241 242 cc `pkg-config --cflags --libs ceed` -o myapp myapp.c 243 244will build `myapp` with libCEED. This can be used with the source or 245installed directories. Most build systems have support for pkg-config. 246 247## Contact 248 249You can reach the libCEED team by emailing [ceed-users@llnl.gov](mailto:ceed-users@llnl.gov) 250or by leaving a comment in the [issue tracker](https://github.com/CEED/libCEED/issues). 251 252## Copyright 253 254The following copyright applies to each file in the CEED software suite, unless 255otherwise stated in the file: 256 257> Copyright (c) 2017, Lawrence Livermore National Security, LLC. Produced at the 258> Lawrence Livermore National Laboratory. LLNL-CODE-734707. All Rights reserved. 259 260See files LICENSE and NOTICE for details. 261 262[ceed-soft]: http://ceed.exascaleproject.org/software/ 263[ecp]: https://exascaleproject.org/exascale-computing-project 264[pkg-config1]: https://en.wikipedia.org/wiki/Pkg-config 265[pkg-config2]: https://people.freedesktop.org/~dbn/pkg-config-guide.html#faq 266
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