, Klaus Iglberger
[aut] (blaze), Georg Georg [aut] (blaze), Tobias Scharpff [aut]
(blaze)| Title: | 'Rcpp' Integration for the 'Blaze' High-Performance 'C++' Math Library |
|---|---|
| Description: | Blaze is an open-source, high-performance 'C++' math library for dense and sparse arithmetic. With its state-of-the-art Smart Expression Template implementation Blaze combines the elegance and ease of use of a domain-specific language with HPC-grade performance, making it one of the most intuitive and fastest 'C++' math libraries available. The 'RcppBlaze' package includes the header files from the 'Blaze' library with disabling some functionalities related to link to the thread and system libraries which make 'RcppBlaze' be a header-only library. Therefore, users do not need to install 'Blaze'. |
| Authors: | Ching-Chuan Chen [aut, cre, ctr]
, Klaus Iglberger
[aut] (blaze), Georg Georg [aut] (blaze), Tobias Scharpff [aut]
(blaze) |
| Maintainer: | Ching-Chuan Chen <[email protected]> |
| License: | BSD_3_clause + file LICENSE |
| Version: | 1.0.1 |
| Built: | 2024-11-05 06:17:49 UTC |
| Source: | CRAN |
RcppBlaze constructs a bridge between R and Blaze.
Blaze is an open-source, high-performance C++ math library for dense and sparse arithmetic. With its state-of-the-art Smart Expression Template implementation Blaze combines the elegance and ease of use of a domain-specific language with HPC-grade performance, making it one of the most intuitive and fastest C++ math libraries available. The RcppBlaze package includes the header files from the Blaze library with disabling some functionalities related to link to the thread and system libraries which make RcppBlaze be a header-only library. Therefore, users do not need to install Blaze.
To use RcppBlaze in your package, there are some important steps:
Include the ‘RcppBlaze.h’ header file, which also includes ‘blaze/Blaze.h’.
Import Rcpp, LinkingTo Rcpp and RcppBlaze by adding these lines to the ‘DESCRIPTION’ file:
Imports: Rcpp (>= 1.0.0) LinkingTo: Rcpp, RcppBlaze
Link against the BLAS and LAPACK libraries, by adding following two lines in the ‘Makevars’ and ‘Makevars.win’ files:
PKG_CXXFLAGS=$(SHLIB_OPENMP_CXXFLAGS) PKG_LIBS = $(LAPACK_LIBS) $(BLAS_LIBS) $(FLIBS) $(SHLIB_OPENMP_CXXFLAGS)
Since there are conflicted definitions between R and blaze which is TRUE and FALSE.
You have to write the initializing function for C/C++ code which the function is named after R_init_YourPackageName
You can refer to our another package, https://github.com/ChingChuan-Chen/RcppLbfgsBlaze for example.
If you would like to enable Boost threads support, you need to import BH package in your DESCRIPTION.
CompressedVector and CompressedMatrix only support int, float and double types.
For RcppBlaze: Ching-Chuan Chen Maintainer: Ching-Chuan Chen <[email protected]> For blaze: Klaus Iglberger, Georg Hager, Christian Godenschwager, Tobias Scharpff
Blaze project: https://bitbucket.org/blaze-lib/blaze.
K. Iglberger, G. Hager, J. Treibig, and U. Ruede: Expression Templates Revisited: A Performance Analysis of Current Methodologies. SIAM Journal on Scientific Computing, 34(2): C42–C69, 2012, doi:10.1137/110830125.
K. Iglberger, G. Hager, J. Treibig, and U. Ruede, High Performance Smart Expression Template Math Libraries. Proceedings of the 2nd International Workshop on New Algorithms and Programming Models for the Manycore Era (APMM 2012) at HPCS 2012, doi:10.1109/HPCSim.2012.6266939.
Useful links:
Report bugs at https://github.com/Chingchuan-chen/RcppBlaze/issues
Set/Get the Number of Threads used in blaze
blaze_set_num_threads(n) blaze_get_num_threads()blaze_set_num_threads(n) blaze_get_num_threads()
n |
The number of threads to set in blaze. |
blaze_get_threads returns an integer and blaze_set_threads returns nothing.
blaze wiki: https://bitbucket.org/blaze-lib/blaze/wiki/Shared%20Memory%20Parallelization.
Set/Get the random number generator for blaze with given seed
blaze_set_seed(seed) blaze_get_seed()blaze_set_seed(seed) blaze_get_seed()
seed |
A positive integer to specify the seed value for the random number generator. |
No return value.
To return the version of Blaze used in RcppBlaze.
blaze_version(single)blaze_version(single)
single |
A logical value indicates which type to return. If TRUE, it returns an integer. If FALSE, it returns a named vector. |
A number or a named vector to represent the version of blaze depending on the input, single.
Blaze header file blaze/system/Version.h.
blaze_version(FALSE)blaze_version(FALSE)
fastLmPure provides the estimates of the linear model based on RcppBlaze.
fastLmPure(X, y, type)fastLmPure(X, y, type)
X |
A model matrix. |
y |
A response vector. |
type |
A integer. 0 is QR solver, 1 is LDLT solver, 2 is LLT sovler and 3 is LU solver. |
fastLm estimates the linear model using the solve.
A list containing coefficients, standard errors, rank of model matrix, degree of freedom of residuals, residuals, the standard deviation of random errors and fitted values.
# according to fastLm example in RcppArmadillo data(trees, package="datasets") flm <- fastLmPure(cbind(1, log(trees$Girth)), log(trees$Volume), 0) print(flm)# according to fastLm example in RcppArmadillo data(trees, package="datasets") flm <- fastLmPure(cbind(1, log(trees$Girth)), log(trees$Volume), 0) print(flm)