ColPack
|
00001 // An example of (Column) compression (by using Acyclic coloring) and indirect recovery for Hessian 00002 /* How to compile this driver manually: 00003 Please make sure that "baseDir" point to the directory (folder) containing the input matrix file, and 00004 s_InputFile should point to the input file that you want to use 00005 To compile the code, replace the Main.cpp file in Main directory with this file 00006 and run "make" in ColPack installation directory. Make will generate "ColPack.exe" executable 00007 Run "ColPack.exe" 00008 00009 Note: If you got "symbol lookup error ... undefined symbol " 00010 Please make sure that your LD_LIBRARY_PATH contains libColPack.so 00011 00012 Return by recovery routine: a matrix 00013 double*** dp3_NewValue; 00014 //*/ 00015 00016 #include "ColPackHeaders.h" 00017 00018 using namespace ColPack; 00019 using namespace std; 00020 00021 #ifndef TOP_DIR 00022 #define TOP_DIR "." 00023 #endif 00024 00025 // baseDir should point to the directory (folder) containing the input file 00026 string baseDir=TOP_DIR; 00027 00028 #include "extra.h" //This .h file contains functions that are used in the below examples: 00029 //ReadMM(), MatrixMultiplication...(), Times2Plus1point5(), displayMatrix() and displayCompressedRowMatrix() 00030 00031 int main() 00032 { 00033 // s_InputFile = baseDir + <name of the input file> 00034 string s_InputFile; //path of the input file 00035 s_InputFile = baseDir; 00036 s_InputFile += DIR_SEPARATOR; s_InputFile += "Graphs"; s_InputFile += DIR_SEPARATOR; s_InputFile += "mtx-spear-head.mtx"; 00037 00038 // Step 1: Determine sparsity structure of the Jacobian. 00039 // This step is done by an AD tool. For the purpose of illustration here, we read the structure from a file, 00040 // and store the structure in a Compressed Row Format. 00041 unsigned int *** uip3_SparsityPattern = new unsigned int **; 00042 double*** dp3_Value = new double**; 00043 int rowCount, columnCount; 00044 ConvertMatrixMarketFormat2RowCompressedFormat(s_InputFile, uip3_SparsityPattern, dp3_Value,rowCount, columnCount); 00045 00046 cout<<"just for debugging purpose, display the 2 matrices: the matrix with SparsityPattern only and the matrix with Value"<<endl; 00047 cout<<fixed<<showpoint<<setprecision(2); //formatting output 00048 cout<<"(*uip3_SparsityPattern)"<<endl; 00049 displayCompressedRowMatrix((*uip3_SparsityPattern),rowCount); 00050 cout<<"(*dp3_Value)"<<endl; 00051 displayCompressedRowMatrix((*dp3_Value),rowCount); 00052 cout<<"Finish ConvertMatrixMarketFormat2RowCompressedFormat()"<<endl; 00053 Pause(); 00054 00055 //Step 2: Obtain the seed matrix via coloring. 00056 double*** dp3_Seed = new double**; 00057 int *ip1_SeedRowCount = new int; 00058 int *ip1_SeedColumnCount = new int; 00059 int* ip1_ColorCount = new int; //The number of distinct colors used to color the graph 00060 00061 //Step 2.1: Read the sparsity pattern of the given Hessian matrix (compressed sparse rows format) 00062 //and create the corresponding graph 00063 GraphColoringInterface *g = new GraphColoringInterface(SRC_MEM_ADOLC, *uip3_SparsityPattern, rowCount); 00064 00065 //Step 2.2: Color the bipartite graph with the specified ordering 00066 g->Coloring("SMALLEST_LAST", "ACYCLIC_FOR_INDIRECT_RECOVERY"); 00067 00068 //Step 2.3 (Option 1): From the coloring information, create and return the seed matrix 00069 (*dp3_Seed) = g->GetSeedMatrix(ip1_SeedRowCount, ip1_SeedColumnCount); 00070 /* Notes: 00071 Step 2.3 (Option 2): From the coloring information, you can also get the vector of colorIDs of vertices 00072 vector<int> vi_VertexColors; 00073 g->GetVertexColors(vi_VertexColors); 00074 */ 00075 cout<<"Finish GenerateSeed()"<<endl; 00076 *ip1_ColorCount = *ip1_SeedColumnCount; 00077 00078 displayMatrix(*dp3_Seed, *ip1_SeedRowCount, *ip1_SeedColumnCount); 00079 Pause(); 00080 00081 // Step 3: Obtain the Hessian-seed matrix product. 00082 // This step will also be done by an AD tool. For the purpose of illustration here, the orginial matrix V 00083 // (for Values) is multiplied with the seed matrix S. The resulting matrix is stored in dp3_CompressedMatrix. 00084 double*** dp3_CompressedMatrix = new double**; 00085 cout<<"Start MatrixMultiplication()"<<endl; 00086 MatrixMultiplication_VxS(*uip3_SparsityPattern, *dp3_Value, rowCount, columnCount, *dp3_Seed, *ip1_SeedColumnCount, dp3_CompressedMatrix); 00087 cout<<"Finish MatrixMultiplication()"<<endl; 00088 00089 displayMatrix(*dp3_CompressedMatrix,rowCount,*ip1_ColorCount); 00090 Pause(); 00091 00092 //Step 4: Recover the numerical values of the original matrix from the compressed representation. 00093 // The new values are store in "dp3_NewValue" 00094 double*** dp3_NewValue = new double**; 00095 HessianRecovery* hr = new HessianRecovery; 00096 hr->IndirectRecover_RowCompressedFormat(g, *dp3_CompressedMatrix, *uip3_SparsityPattern, dp3_NewValue); 00097 cout<<"Finish Indirect Recover()"<<endl; 00098 00099 displayCompressedRowMatrix(*dp3_NewValue,rowCount); 00100 Pause(); 00101 00102 //Check for consistency, make sure the values in the 2 matrices are the same. 00103 if (CompressedRowMatricesAreEqual(*dp3_Value, *dp3_NewValue, rowCount,0,1)) cout<< "*dp3_Value == dp3_NewValue"<<endl; 00104 else cout<< "*dp3_Value != dp3_NewValue"<<endl; 00105 00106 00107 Pause(); 00108 00109 //Deallocate memory using functions in Utilities/MatrixDeallocation.h 00110 00111 free_2DMatrix(uip3_SparsityPattern, rowCount); 00112 uip3_SparsityPattern=NULL; 00113 00114 free_2DMatrix(dp3_Value, rowCount); 00115 dp3_Value=NULL; 00116 00117 delete dp3_Seed; 00118 dp3_Seed = NULL; 00119 00120 delete ip1_SeedRowCount; 00121 ip1_SeedRowCount=NULL; 00122 00123 delete ip1_SeedColumnCount; 00124 ip1_SeedColumnCount = NULL; 00125 00126 free_2DMatrix(dp3_CompressedMatrix, rowCount); 00127 dp3_CompressedMatrix = NULL; 00128 00129 delete ip1_ColorCount; 00130 ip1_ColorCount = NULL; 00131 00132 delete hr; 00133 hr = NULL; 00134 00135 delete dp3_NewValue; 00136 dp3_NewValue=NULL; 00137 00138 delete g; 00139 g=NULL; 00140 00141 return 0; 00142 }