| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154 | 
							- Bench Template Library
 
- ****************************************
 
- Introduction :
 
- The aim of this project is to compare the performance
 
- of available numerical libraries. The code is designed
 
- as generic and modular as possible. Thus, adding new
 
- numerical libraries or new numerical tests should
 
- require minimal effort.
 
- *****************************************
 
- Installation :
 
- BTL uses cmake / ctest:
 
- 1 - create a build directory:
 
-   $ mkdir build
 
-   $ cd build
 
- 2 - configure:
 
-   $ ccmake ..
 
- 3 - run the bench using ctest:
 
-   $ ctest -V
 
- You can run the benchmarks only on libraries matching a given regular expression:
 
-   ctest -V -R <regexp>
 
- For instance:
 
-   ctest -V -R eigen2
 
- You can also select a given set of actions defining the environment variable BTL_CONFIG this way:
 
-   BTL_CONFIG="-a action1{:action2}*" ctest -V
 
- An example:
 
-   BTL_CONFIG="-a axpy:vector_matrix:trisolve:ata" ctest -V -R eigen2
 
- Finally, if bench results already exist (the bench*.dat files) then they merges by keeping the best for each matrix size. If you want to overwrite the previous ones you can simply add the "--overwrite" option:
 
-   BTL_CONFIG="-a axpy:vector_matrix:trisolve:ata --overwrite" ctest -V -R eigen2
 
- 4 : Analyze the result. different data files (.dat) are produced in each libs directories.
 
-  If gnuplot is available, choose a directory name in the data directory to store the results and type:
 
-         $ cd data
 
-         $ mkdir my_directory
 
-         $ cp ../libs/*/*.dat my_directory
 
-  Build the data utilities in this (data) directory
 
-         make
 
-  Then you can look the raw data,
 
-         go_mean my_directory
 
-  or smooth the data first :
 
- 	smooth_all.sh my_directory
 
- 	go_mean my_directory_smooth
 
- *************************************************
 
- Files and directories :
 
-  generic_bench : all the bench sources common to all libraries
 
-  actions : sources for different action wrappers (axpy, matrix-matrix product) to be tested.
 
-  libs/* : bench sources specific to each tested libraries.
 
-  machine_dep : directory used to store machine specific Makefile.in
 
-  data : directory used to store gnuplot scripts and data analysis utilities
 
- **************************************************
 
- Principles : the code modularity is achieved by defining two concepts :
 
-  ****** Action concept : This is a class defining which kind
 
-   of test must be performed (e.g. a matrix_vector_product).
 
- 	An Action should define the following methods :
 
-         *** Ctor using the size of the problem (matrix or vector size) as an argument
 
- 	    Action action(size);
 
-         *** initialize : this method initialize the calculation (e.g. initialize the matrices and vectors arguments)
 
- 	    action.initialize();
 
- 	*** calculate : this method actually launch the calculation to be benchmarked
 
- 	    action.calculate;
 
- 	*** nb_op_base() : this method returns the complexity of the calculate method (allowing the mflops evaluation)
 
-         *** name() : this method returns the name of the action (std::string)
 
-  ****** Interface concept : This is a class or namespace defining how to use a given library and
 
-   its specific containers (matrix and vector). Up to now an interface should following types
 
- 	*** real_type : kind of float to be used (float or double)
 
- 	*** stl_vector : must correspond to std::vector<real_type>
 
- 	*** stl_matrix : must correspond to std::vector<stl_vector>
 
- 	*** gene_vector : the vector type for this interface        --> e.g. (real_type *) for the C_interface
 
- 	*** gene_matrix : the matrix type for this interface        --> e.g. (gene_vector *) for the C_interface
 
- 	+ the following common methods
 
-         *** free_matrix(gene_matrix & A, int N)  dealocation of a N sized gene_matrix A
 
-         *** free_vector(gene_vector & B)  dealocation of a N sized gene_vector B
 
-         *** matrix_from_stl(gene_matrix & A, stl_matrix & A_stl) copy the content of an stl_matrix A_stl into a gene_matrix A.
 
- 	     The allocation of A is done in this function.
 
- 	*** vector_to_stl(gene_vector & B, stl_vector & B_stl)  copy the content of an stl_vector B_stl into a gene_vector B.
 
- 	     The allocation of B is done in this function.
 
-         *** matrix_to_stl(gene_matrix & A, stl_matrix & A_stl) copy the content of an gene_matrix A into an stl_matrix A_stl.
 
-              The size of A_STL must corresponds to the size of A.
 
-         *** vector_to_stl(gene_vector & A, stl_vector & A_stl) copy the content of an gene_vector A into an stl_vector A_stl.
 
-              The size of B_STL must corresponds to the size of B.
 
- 	*** copy_matrix(gene_matrix & source, gene_matrix & cible, int N) : copy the content of source in cible. Both source
 
- 		and cible must be sized NxN.
 
- 	*** copy_vector(gene_vector & source, gene_vector & cible, int N) : copy the content of source in cible. Both source
 
-  		and cible must be sized N.
 
- 	and the following method corresponding to the action one wants to be benchmarked :
 
- 	***  matrix_vector_product(const gene_matrix & A, const gene_vector & B, gene_vector & X, int N)
 
- 	***  matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N)
 
-         ***  ata_product(const gene_matrix & A, gene_matrix & X, int N)
 
- 	***  aat_product(const gene_matrix & A, gene_matrix & X, int N)
 
-         ***  axpy(real coef, const gene_vector & X, gene_vector & Y, int N)
 
-  The bench algorithm (generic_bench/bench.hh) is templated with an action itself templated with
 
-  an interface. A typical main.cpp source stored in a given library directory libs/A_LIB
 
-  looks like :
 
-  bench< AN_ACTION < AN_INTERFACE > >( 10 , 1000 , 50 ) ;
 
-  this function will produce XY data file containing measured  mflops as a function of the size for 50
 
-  sizes between 10 and 10000.
 
-  This algorithm can be adapted by providing a given Perf_Analyzer object which determines how the time
 
-  measurements must be done. For example, the X86_Perf_Analyzer use the asm rdtsc function and provides
 
-  a very fast and accurate (but less portable) timing method. The default is the Portable_Perf_Analyzer
 
-  so
 
-  bench< AN_ACTION < AN_INTERFACE > >( 10 , 1000 , 50 ) ;
 
-  is equivalent to
 
-  bench< Portable_Perf_Analyzer,AN_ACTION < AN_INTERFACE > >( 10 , 1000 , 50 ) ;
 
-  If your system supports it we suggest to use a mixed implementation (X86_perf_Analyzer+Portable_Perf_Analyzer).
 
-  replace
 
-      bench<Portable_Perf_Analyzer,Action>(size_min,size_max,nb_point);
 
-  with
 
-      bench<Mixed_Perf_Analyzer,Action>(size_min,size_max,nb_point);
 
-  in generic/bench.hh
 
- .
 
 
  |