xref: /libCEED/README.md (revision 9ad453579b4f8e35becf925ceedf519a25efe885)
1# libCEED: the CEED API Library
2
3[![Build Status](https://travis-ci.org/CEED/libCEED.svg?branch=master)](https://travis-ci.org/CEED/libCEED)
4[![Code Coverage](https://codecov.io/gh/CEED/libCEED/branch/master/graphs/badge.svg)](https://codecov.io/gh/CEED/libCEED/)
5[![License](https://img.shields.io/badge/License-BSD%202--Clause-orange.svg)](https://opensource.org/licenses/BSD-2-Clause)
6[![Doxygen](https://codedocs.xyz/CEED/libCEED.svg)](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/tmpl`         | Backend template, delegates to `/cpu/self/ref/blocked` |
92| `/cpu/self/ref/memcheck` | Memcheck backend, undefined value checks          |
93| `/cpu/self/avx/serial`   | Serial AVX implementation                         |
94| `/cpu/self/avx/blocked`  | Blocked AVX implementation                        |
95| `/cpu/self/xsmm/serial`  | Serial LIBXSMM implementation                     |
96| `/cpu/self/xsmm/blocked` | Blocked LIBXSMM implementation                    |
97| `/cpu/occa`              | Serial OCCA kernels                               |
98| `/gpu/occa`              | CUDA OCCA kernels                                 |
99| `/omp/occa`              | OpenMP OCCA kernels                               |
100| `/ocl/occa`              | OpenCL OCCA kernels                               |
101| `/gpu/cuda/ref`          | Reference pure CUDA kernels                       |
102| `/gpu/cuda/reg`          | Pure CUDA kernels using one thread per element    |
103| `/gpu/magma`             | CUDA MAGMA kernels                                |
104
105
106The `/cpu/self/*/serial` backends process one element at a time and are intended for meshes
107with a smaller number of high order elements. The `/cpu/self/*/blocked` backends process
108blocked batches of eight interlaced elements and are intended for meshes with higher numbers
109of elements.
110
111The `/cpu/self/ref/*` backends are written in pure C and provide basic functionality.
112
113The `/cpu/self/avx/*` backends rely upon AVX instructions to provide vectorized CPU performance.
114
115The `/cpu/self/xsmm/*` backends rely upon the [LIBXSMM](http://github.com/hfp/libxsmm) package
116to provide vectorized CPU performance. The LIBXSMM backend does not use BLAS or MKL; however,
117if LIBXSMM was linked to MKL, this can be specified with the compilation flag `MKL=1`.
118
119The `/cpu/self/ref/memcheck` backend relies upon the [Valgrind](http://valgrind.org/) Memcheck tool
120to help verify that user QFunctions have no undefined values. To use, run your code with
121Valgrind and the Memcheck backend, e.g. `valgrind ./build/ex1 -ceed /cpu/self/ref/memcheck`.
122
123The `/*/occa` backends rely upon the [OCCA](http://github.com/libocca/occa) package to provide
124cross platform performance.
125
126The `/gpu/cuda/*` backends provide GPU performance strictly using CUDA.
127
128The `/gpu/magma` backend relies upon the [MAGMA](https://bitbucket.org/icl/magma) package.
129
130## Examples
131
132libCEED comes with several examples of its usage, ranging from standalone C
133codes in the `/examples/ceed` directory to examples based on external packages,
134such as MFEM, PETSc, and Nek5000. Nek5000 v18.0 or greater is required.
135
136To build the examples, set the `MFEM_DIR`, `PETSC_DIR` and `NEK5K_DIR` variables
137and run:
138
139```console
140# libCEED examples on CPU and GPU
141cd examples/ceed
142make
143./ex1 -ceed /cpu/self
144./ex1 -ceed /gpu/occa
145cd ../..
146
147# MFEM+libCEED examples on CPU and GPU
148cd examples/mfem
149make
150./bp1 -ceed /cpu/self -no-vis
151./bp1 -ceed /gpu/occa -no-vis
152cd ../..
153
154# PETSc+libCEED examples on CPU and GPU
155cd examples/petsc
156make
157./bp1 -ceed /cpu/self
158./bp1 -ceed /gpu/occa
159cd ../..
160
161cd navier-stokes
162make
163./navierstokes -ceed /cpu/self
164./navierstokes -ceed /gpu/occa
165cd ../..
166
167# Nek+libCEED examples on CPU and GPU
168cd examples/nek5000
169./make-nek-examples.sh
170./run-nek-example.sh -ceed /cpu/self -b 3
171./run-nek-example.sh -ceed /gpu/occa -b 3
172cd ../..
173```
174
175The above code assumes a GPU-capable machine with the OCCA backend
176enabled. Depending on the available backends, other Ceed resource specifiers can
177be provided with the `-ceed` option.
178
179## Benchmarks
180
181A sequence of benchmarks for all enabled backends can be run using
182
183```console
184make benchmarks
185```
186
187The results from the benchmarks are stored inside the `benchmarks/` directory
188and they can be viewed using the commands (requires python with matplotlib):
189
190```console
191cd benchmarks
192python postprocess-plot.py petsc-bp1-*-output.txt
193python postprocess-plot.py petsc-bp3-*-output.txt
194```
195
196Using the `benchmarks` target runs a comprehensive set of benchmarks which may
197take some time to run. Subsets of the benchmarks can be run using targets such
198as `make bench-petsc-bp1`, or `make bench-petsc-bp3`.
199
200For more details about the benchmarks, see
201[`benchmarks/README.md`](benchmarks/README.md)
202
203
204## Install
205
206To install libCEED, run
207
208    make install prefix=/usr/local
209
210or (e.g., if creating packages),
211
212    make install prefix=/usr DESTDIR=/packaging/path
213
214Note that along with the library, libCEED installs kernel sources, e.g. OCCA
215kernels are installed in `$prefix/lib/okl`. This allows the OCCA backend to
216build specialized kernels at run-time. In a normal setting, the kernel sources
217will be found automatically (relative to the library file `libceed.so`).
218However, if that fails (e.g. if `libceed.so` is moved), one can copy (cache) the
219kernel sources inside the user OCCA directory, `~/.occa` using
220
221    $(OCCA_DIR)/bin/occa cache ceed $(CEED_DIR)/lib/okl/*.okl
222
223This will allow OCCA to find the sources regardless of the location of the CEED
224library. One may occasionally need to clear the OCCA cache, which can be accomplished
225by removing the `~/.occa` directory or by calling `$(OCCA_DIR)/bin/occa clear -a`.
226
227### pkg-config
228
229In addition to library and header, libCEED provides a [pkg-config][pkg-config1]
230file that can be used to easily compile and link. [For example][pkg-config2], if
231`$prefix` is a standard location or you set the environment variable
232`PKG_CONFIG_PATH`,
233
234    cc `pkg-config --cflags --libs ceed` -o myapp myapp.c
235
236will build `myapp` with libCEED.  This can be used with the source or
237installed directories.  Most build systems have support for pkg-config.
238
239## Contact
240
241You can reach the libCEED team by emailing [ceed-users@llnl.gov](mailto:ceed-users@llnl.gov)
242or by leaving a comment in the [issue tracker](https://github.com/CEED/libCEED/issues).
243
244## Copyright
245
246The following copyright applies to each file in the CEED software suite, unless
247otherwise stated in the file:
248
249> Copyright (c) 2017, Lawrence Livermore National Security, LLC. Produced at the
250> Lawrence Livermore National Laboratory. LLNL-CODE-734707. All Rights reserved.
251
252See files LICENSE and NOTICE for details.
253
254[ceed-soft]:   http://ceed.exascaleproject.org/software/
255[ecp]:         https://exascaleproject.org/exascale-computing-project
256[pkg-config1]: https://en.wikipedia.org/wiki/Pkg-config
257[pkg-config2]: https://people.freedesktop.org/~dbn/pkg-config-guide.html#faq
258