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<<<<<<< HEAD 88| CEED resource | Backend | 89| :----------------------- | :------------------------------------------------ | 90| `/cpu/self/ref/serial` | Serial reference implementation | 91| `/cpu/self/ref/blocked` | Blocked refrence implementation | 92| `/cpu/self/tmpl` | Backend template, delegates to `/cpu/self/ref/blocked` | 93| `/cpu/self/ref/memcheck` | Memcheck backend, undefined value checks | 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/magma` | CUDA MAGMA kernels | 105======= 106| CEED resource | Backend | 107| :---------------------------- | :----------------------------------------------------- | 108| `/cpu/self/ref/serial` | Serial reference implementation | 109| `/cpu/self/ref/blocked` | Blocked refrence implementation | 110| `/cpu/self/ref/blocked/full` | Blocked refrence implementation with full Evectors | 111| `/cpu/self/tmpl` | Backend template, delegates to `/cpu/self/ref/blocked` | 112| `/cpu/self/avx/serial` | Serial AVX implementation | 113| `/cpu/self/avx/blocked` | Blocked AVX implementation | 114| `/cpu/self/xsmm/serial` | Serial LIBXSMM implementation | 115| `/cpu/self/xsmm/blocked` | Blocked LIBXSMM implementation | 116| `/cpu/occa` | Serial OCCA kernels | 117| `/gpu/occa` | CUDA OCCA kernels | 118| `/omp/occa` | OpenMP OCCA kernels | 119| `/ocl/occa` | OpenCL OCCA kernels | 120| `/gpu/cuda/ref` | Reference pure CUDA kernels | 121| `/gpu/cuda/reg` | Pure CUDA kernels using one thread per element | 122| `/gpu/magma` | CUDA MAGMA kernels | 123>>>>>>> Include full evec blocked backend 124 125 126The `/cpu/self/*/serial` backends process one element at a time and are intended for meshes 127with a smaller number of high order elements. The `/cpu/self/*/blocked` backends process 128blocked batches of eight interlaced elements and are intended for meshes with higher numbers 129of elements. 130 131The `/cpu/self/ref/*` backends are written in pure C and provide basic functionality. 132 133The `/cpu/self/avx/*` backends rely upon AVX instructions to provide vectorized CPU performance. 134 135The `/cpu/self/xsmm/*` backends rely upon the [LIBXSMM](http://github.com/hfp/libxsmm) package 136to provide vectorized CPU performance. The LIBXSMM backend does not use BLAS or MKL; however, 137if LIBXSMM was linked to MKL, this can be specified with the compilation flag `MKL=1`. 138 139The `/cpu/self/ref/memcheck` backend relies upon the [Valgrind](http://valgrind.org/) Memcheck tool 140to help verify that user QFunctions have no undefined values. To use, run your code with 141Valgrind and the Memcheck backend, e.g. `valgrind ./build/ex1 -ceed /cpu/self/ref/memcheck`. 142 143The `/*/occa` backends rely upon the [OCCA](http://github.com/libocca/occa) package to provide 144cross platform performance. 145 146The `/gpu/cuda/*` backends provide GPU performance strictly using CUDA. 147 148The `/gpu/magma` backend relies upon the [MAGMA](https://bitbucket.org/icl/magma) package. 149 150## Examples 151 152libCEED comes with several examples of its usage, ranging from standalone C 153codes in the `/examples/ceed` directory to examples based on external packages, 154such as MFEM, PETSc, and Nek5000. Nek5000 v18.0 or greater is required. 155 156To build the examples, set the `MFEM_DIR`, `PETSC_DIR` and `NEK5K_DIR` variables 157and run: 158 159```console 160# libCEED examples on CPU and GPU 161cd examples/ceed 162make 163./ex1 -ceed /cpu/self 164./ex1 -ceed /gpu/occa 165cd ../.. 166 167# MFEM+libCEED examples on CPU and GPU 168cd examples/mfem 169make 170./bp1 -ceed /cpu/self -no-vis 171./bp1 -ceed /gpu/occa -no-vis 172cd ../.. 173 174# PETSc+libCEED examples on CPU and GPU 175cd examples/petsc 176make 177./bp1 -ceed /cpu/self 178./bp1 -ceed /gpu/occa 179cd ../.. 180 181cd navier-stokes 182make 183./navierstokes -ceed /cpu/self 184./navierstokes -ceed /gpu/occa 185cd ../.. 186 187# Nek+libCEED examples on CPU and GPU 188cd examples/nek5000 189./make-nek-examples.sh 190./run-nek-example.sh -ceed /cpu/self -b 3 191./run-nek-example.sh -ceed /gpu/occa -b 3 192cd ../.. 193``` 194 195The above code assumes a GPU-capable machine with the OCCA backend 196enabled. Depending on the available backends, other Ceed resource specifiers can 197be provided with the `-ceed` option. 198 199## Benchmarks 200 201A sequence of benchmarks for all enabled backends can be run using 202 203```console 204make benchmarks 205``` 206 207The results from the benchmarks are stored inside the `benchmarks/` directory 208and they can be viewed using the commands (requires python with matplotlib): 209 210```console 211cd benchmarks 212python postprocess-plot.py petsc-bp1-*-output.txt 213python postprocess-plot.py petsc-bp3-*-output.txt 214``` 215 216Using the `benchmarks` target runs a comprehensive set of benchmarks which may 217take some time to run. Subsets of the benchmarks can be run using targets such 218as `make bench-petsc-bp1`, or `make bench-petsc-bp3`. 219 220For more details about the benchmarks, see 221[`benchmarks/README.md`](benchmarks/README.md) 222 223 224## Install 225 226To install libCEED, run 227 228 make install prefix=/usr/local 229 230or (e.g., if creating packages), 231 232 make install prefix=/usr DESTDIR=/packaging/path 233 234Note that along with the library, libCEED installs kernel sources, e.g. OCCA 235kernels are installed in `$prefix/lib/okl`. This allows the OCCA backend to 236build specialized kernels at run-time. In a normal setting, the kernel sources 237will be found automatically (relative to the library file `libceed.so`). 238However, if that fails (e.g. if `libceed.so` is moved), one can copy (cache) the 239kernel sources inside the user OCCA directory, `~/.occa` using 240 241 $(OCCA_DIR)/bin/occa cache ceed $(CEED_DIR)/lib/okl/*.okl 242 243This will allow OCCA to find the sources regardless of the location of the CEED 244library. One may occasionally need to clear the OCCA cache, which can be accomplished 245by removing the `~/.occa` directory or by calling `$(OCCA_DIR)/bin/occa clear -a`. 246 247### pkg-config 248 249In addition to library and header, libCEED provides a [pkg-config][pkg-config1] 250file that can be used to easily compile and link. [For example][pkg-config2], if 251`$prefix` is a standard location or you set the environment variable 252`PKG_CONFIG_PATH`, 253 254 cc `pkg-config --cflags --libs ceed` -o myapp myapp.c 255 256will build `myapp` with libCEED. This can be used with the source or 257installed directories. Most build systems have support for pkg-config. 258 259## Contact 260 261You can reach the libCEED team by emailing [ceed-users@llnl.gov](mailto:ceed-users@llnl.gov) 262or by leaving a comment in the [issue tracker](https://github.com/CEED/libCEED/issues). 263 264## Copyright 265 266The following copyright applies to each file in the CEED software suite, unless 267otherwise stated in the file: 268 269> Copyright (c) 2017, Lawrence Livermore National Security, LLC. Produced at the 270> Lawrence Livermore National Laboratory. LLNL-CODE-734707. All Rights reserved. 271 272See files LICENSE and NOTICE for details. 273 274[ceed-soft]: http://ceed.exascaleproject.org/software/ 275[ecp]: https://exascaleproject.org/exascale-computing-project 276[pkg-config1]: https://en.wikipedia.org/wiki/Pkg-config 277[pkg-config2]: https://people.freedesktop.org/~dbn/pkg-config-guide.html#faq 278
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