/** \mainpage High performance Spherical Harmonic Transform for numerical simulations. * * SHTns is a high performance library for Spherical Harmonic Transform written in C, aimed at numerical simulation (fluid flows, mhd, ...) in spherical geometries.\n * * Main features : * - \link bench blazingly fast\endlink * - distributed under the open source \link license CeCILL License\endlink (GPL compatible) * - both scalar and \link vsh vector transforms\endlink * - backward and forward (synthesis and analysis) functions * - flexible truncation * - spatial data can be stored in latitude-major or longitude-major order arrays. * - various conventions (normalization and Condon-Shortley phase) * - can be used from Fortran, c/c++, and Python programs * - a highly efficient Gauss algorithm working with Gauss nodes (based on Gauss-Legendre quadrature) * - an algorithm using DCT for regular nodes (based on a generalized Fejer quadrature) * - support for SSE2, SSE3 and AVX vectorization with gcc. * - parallel transforms with OpenMP (for Gauss grid only). * - synthesis (inverse transform) at any coordinate (not constrained to a grid) useful for rendering purposes. * - ability to choose the optimal spatial sizes for a given spherical harmonic truncation. * - on-the-fly transforms : saving memory and bandwidth, and can even be faster depending on architecture. * - accurate up to spherical harmonic degree l=16383 (at least). * - \link rotation rotation functions\endlink to rotate spherical harmonics (beta). * - \link operators special spectral operator\endlink functions that do not require a transform (multiply by cos(theta)...) . * - scalar transforms for complex spatial fields. * * Using DCT acceleration and other classical \link opt optimizations\endlink, it is intended to be \link bench very fast\endlink. * * It requires the FFTW library for Fast Fourier Transforms. * * If you use SHTns for research work, please cite the paper: Efficient Spherical Harmonic Transforms aimed at pseudo-spectral numerical simulations, * also available from arXiv. * * If you accept the open source \link license CeCILL License\endlink (GPL compatible french License), you can download SHTns. * * Please report bugs and feature request on the issue tracker. * * \see shtns.h for the definitions of variables, macros and functions. * \see The example programs (in \link SHT_example.f Fortran \endlink, \link SHT_example.c C \endlink and \link SHT_example.py Python \endlink) to get started. * \see The organisation of data used by SHTns is described in \ref spat. * \see The description of \ref opt. * * \author SHTns is written by Nathanael Schaeffer (CNRS). Email: nathanael.schaeffer@ujf-grenoble.fr * * \image html logo_cnrs_small.png * */ /** \page compil Compiling and installing SHTns To compile SHTns, you need a C compiler and the FFTW library version 3.0 (or better 3.3) or later, carefully optimized and installed. On modern x86 processors, we recommend using GCC 4.0 or later as it produces the fastest vectorized code. First run \code ./configure --help \endcode to see the available configure options. Then, for example run \code ./configure --prefix=$HOME --enable-openmp \endcode if you want to install the multi-threaded transform library to $HOME/lib and the headers to $HOME/include. To install the Python extension, see \ref python. The configure script will detect your FFTW library capabilities and other system dependant features. You may optionally adapt the resulting \c Makefile and \c sht_config.h to your architecture and compiler. Then compile with \c make and install with \c make \c install. SHTns requires FFTW, which can be installed as a compiled package on many operating systems. However, we recommend to compile it and install it yourself, as it can lead to much better performance. If FFTW has not been compiled and tuned carefully for your machine, you may get bad performance with SHTns (down to 50% slower !). Furthermore, if FFTW is more recent than 3.3, or has not been configured with \c --enable-openmp (see below), SHTns cannot do the Fourier transform part in parallel. \section fftw Compiling and installing FFTW You can download the latest FFTW package from http://www.fftw.org, compile it and install it. In order to use the parallel transforms, make sure to pass \c --enable-openmp to the configure script. We also recommend passing \c --enable-sse2 or \c --enable-avx to the configure script on x86 architectures. You may also take a look at the FFTW documentation for compilation advice. For example: \code ./configure --enable-openmp --enable-shared --enable-avx --prefix=$HOME/usr make make install \endcode That's it, FFTW is now installed and ready for use. \subsection mkl Using MKL instead of FFTW SHTns can use MKL instead of FFTW. To do this, pass \c --enable-mkl to the configure script. Performance can be slightly better, but there is no DCT support, so only gauss grid is available. \note Currently the call of MKL through the fftw wrappers is not thread safe. The user is responsible for working around this MKL problem as indicated by intel. If you want to call SHT function from multiple threads, you must tell MKL how many threads you will use BEFORE initializing shtns : \code #include "fftw3_mkl.h" fftw3_mkl.number_of_user_threads = 4; sht = shtns_create(...); ... \endcode \section makefile Preparing the Makefile Run \c ./configure in the SHTns directory. You can use \c --enable-openmp to enable multi-threaded transforms, and \c --enable-long-double to (maybe) increase accuracy during initialization (not recommended). You can then edit the resulting Makefile: \li set \c PREFIX= to the desired install path. \li further editing is needed if you don't use gcc \section config Changing default options Simple tunings can be done by passing options to \c ./configure (see \c ./configure \c --help) \section comp Compiling \li type \code make \endcode to compile SHTns. it will produce the library \c libshtns.a \li type \code make PREFIX=/usr/local install \endcode to install the library in your system (set PREFIX to the desired location, default is $HOME). \li type \code make docs \endcode to generate this documentation, placed in the doc/html/ subdirectory. \li type \code make time_SHT \endcode to build the test and timing program. */ /** \page spat Spatial data layouts and grids used by SHTns The angular coordinates on a spherical shell are the co-latitude \f$ \theta \f$ and the longitude \f$ \phi \f$. The spatial discretization is defined by a call to \ref shtns_init; or to \ref shtns_set_grid or \ref shtns_set_grid_auto after \ref shtns_create. A field \e A (or one of its component in case of a vector field) is discretized on an ordered grid, which consists of - NPHI equally spaced nodes in longitude, spanning the range of angle between 0 (included) and \f$2\pi\f$/MRES (excluded), - NLAT gauss nodes or equally spaced nodes (depending on \ref shtns_type) in latitude, spanning angles from 0 to \f$ \pi \f$. There are constraints on the sizes NLAT and NPHI. The sampling theorem requires NPHI > 2*MMAX, with MMAX the highest Fourier mode to be resolved. Similarly NLAT > LMAX is required for a Gauss-Legendre quadrature. When dealing with non-linear equation, or more generally when analysing data that is not band-limited to LMAX and/or MMAX, anti-aliasing constraints exist. For a given non-linear order of the equation N (typically 2), the anti-aliasing conditions are : - NPHI > (N+1)*MMAX - NLAT > (N+1)*LMAX/2 for Gauss-Legendre quadrature - NLAT > N*LMAX for our DCT quadrature Furthermore, FFT is more efficient for certain values of NPHI and/or NLAT. If you do not require specific NLAT or NPHI, you can let SHTns choose them for you, by using \ref shtns_set_grid_auto with nphi and/or nlat set to zero. Identifying a grid point with its indices \c it and \c ip in latitudinal and longitudinal direction respectively (indices start at 0), one has : - \f$ \theta \f$ = \c acos(ct[it]) where \c ct = \ref shtns_info.ct is initialized by the call to \ref shtns_init - \f$ \phi \f$ = \c ip * 2\f$\pi\f$/(NPHI*MRES) and \ref PHI_RAD and \ref PHI_DEG can be used to get the phi angle corresponding to \c ip. - How to access \f$ A(\theta,\phi) \f$ depends on the data layout, but it is always a contiguous array of double precision floating point values (64 bit) Currently, three data layouts are supported. \ref phi_fast, \ref theta_fast, and \ref native. \section phi_fast Contiguous longitudes In this layout, increasing longitudes are stored next to each other for each latitude. That is \f$ A(\theta,\phi) \f$ = \c A[it*NPHI + ip] in C or \c A(ip,it) in Fortran. Use \ref SHT_PHI_CONTIGUOUS to instruct \ref shtns_init to use this spatial data layout : \code shtns_init ( sht_gauss | SHT_PHI_CONTIGUOUS, ... ) \endcode will tell shtns to precompute everything for a gauss grid, and spatial data stored with longitude varying fastest. \section theta_fast Contiguous latitudes In this layout, increasing latitude are stored next to each other for each longitude. That is \f$ A(\theta,\phi) \f$ = \c A[ip*NLAT + it] in C or \c A(it,ip) in Fortran. Use \ref SHT_THETA_CONTIGUOUS to instruct \ref shtns_init to use this spatial data layout. \section native Native layout The native way of storing spatial field data (which will help you achieve the best performance with SHTns) is the same as the \ref theta_fast layout, except that it requires you to allocate slightly more memory for a field than the NLAT*NPHI double values. Namely NLAT*(NPHI/2+1)*2 doubles are required (instead of NLAT*NPHI) to be able tu use the in-place FFT of FFTW. In Fortran this means you will allocate data as if the phi direction had (NPHI/2+1)*2 points instead fo NPHI. The additional space, is located at the end of the useful data, and you don't need to worry about it. To instruct \ref shtns_init that your spatial data has been set up using this layout, use \ref SHT_NATIVE_LAYOUT. \note One must be careful when allocating spatial data, as the Fourier transform requires some additional space.\n Precisely, the number of required \c double is \ref NSPAT_ALLOC = NLAT*(NPHI/2+1)*2. The first NLAT*NPHI values are the spatial data. \note In addition, spatial data must be allocated using the \c fftw_malloc function, for example using : \code A = fftw_malloc( NSPAT_ALLOC * sizeof(double) );\endcode \note It is not recommended to use the native layout with Fortran or Python. */ /** \page spec Spherical Harmonics storage and normalization \section spec_data Spherical Harmonic coefficients layout The collection of Alm (spherical harmonics coefficient of degree \e l and order \e m) is stored in an array of \c complex \c double floating point values. The spherical harmonic truncation is defined by a call to \ref shtns_init or to \ref shtns_create which returns an \c shtns_cfg object (pointer to \ref shtns_info) from which the the size of the array, \ref shtns_info.nlm, can be read (see examples). The field \em A is decomposed on the basis of spherical harmonics Ylm (degree \e l, order \e m) : \f[ A(\theta,\phi) = \sum_{l,m} A_l^m Y_l^m(\theta,\phi)\f] The series is truncated at degree LMAX and order MMAX*MRES, and only order that are multiple of MRES are described. The NLM coefficients Alm are stored in a one-dimensional array, grouped by \e m.\n The details of the storage may depend on the algorithm, and to access a particular coefficient, you should always use the following macros : - \ref LM(l,m) gives the index in the array for coefficient of degree \e l and order \e m. - \ref LiM(l,im) gives the index in the array for coefficient of degree \e l and order \e im*MRES. Hence \c Alm[LM(l,m)] is the (complex) SH coefficient of degree \e l and order \e m. \note Since SHTns only deals with real spatial data, the Spherical Harmonic coefficients with negative \e m are related to the complex conjugate of the positive \e m coefficients : \f$ A_l^{-m} = (-1)^{m} (A_l^m)^*\f$. For efficiency purposes, only the coefficients with positive \e m are stored. \note There is no test on bounds, so that LM(l,m) with \e l or \e m that is not described, will give undefined result (in particular for an \e m that is not a multiple of \c MRES) To perform loops on all coefficients, use the macros \ref LM_LOOP and \ref LM_L_LOOP in combination of the arrays \ref shtns_info.li which give the degree \e l and functions of it for any array index. \section Allocation Allocation for a SH description is simply done with : \code Alm = fftw_malloc( NLM * sizeof(complex double) );\endcode The use of fftw_malloc ensures proper alignment of data for SSE vectorization (if fftw has been properly compiled with --enable-sse2 or --enable-avx). \section norm Normalization Several normalizations for the spherical harmonics exist (details on wikipedia). SHTns lets you choose one of the following :
\f$\ell_{max}\f$ | shtools 2.8 (Gauss) | libpsht (1 thread) | SpharmonicKit2 2.7 (fast) | SHTns 2.1 (1 thread, Gauss) | SpharmonicKit2/SHTns |
63 | 1.14 ms | 1.05 ms | 1.1 ms | 0.09 ms | 12.2 |
127 | 3.5 ms | 4.7 ms | 5.5 ms | 0.60 ms | 9.2 |
255 | 28 ms | 27 ms | 21 ms | 4.2 ms | 5.0 |
511 | 200 ms | 162 ms | 110 ms | 28 ms | 3.9 |
1023 | 1.8 s | 850 ms | 600 ms | 216 ms | 2.8 |
2047 | 13.0 s | 4.4 s | NA (out of memory) | 1.6 s | NA |
4095 | NA (seg fault) | 30.5 s | 11.8 s | NA |
\f$\ell_{max}\f$ | libpsht 20110131 | SHTns 2.2.1 | libpsht/SHTns |
63 | 5.0 ms | 0.05 ms | 100 |
127 | 5.4 ms | 0.22 ms | 24.5 |
255 | 8.5 ms | 1.4 ms | 6.1 |
511 | 23.5 ms | 6.5 ms | 3.6 |
1023 | 125 ms | 43 ms | 2.9 |
2047 | 700 ms | 331 ms | 2.1 |
4095 | 3.0 s | 2.0 s | 1.5 |
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