我们有一个运行PARDISO求解器的代码。静态链接此代码时，分解分解步骤比动态链接相同代码时快2倍。
以下是在两种情况下从CMake获得的链接线（我已经使用MKL链接线顾问程序来帮助我定义参数）：
静态链接：
/opt/intel/compilers_and_libraries_2016/linux/bin/intel64/icpc -rdynamic CMakeFiles/simplesolver.dir/pardiso_sym_c.cpp.o -o simplesolver -Wl,--start-group /opt/intel/compilers_and_libraries_2016/linux/mkl/lib/intel64/libmkl_intel_lp64.a /opt/intel/compilers_and_libraries_2016/linux/mkl/lib/intel64/libmkl_intel_thread.a /opt/intel/compilers_and_libraries_2016/linux/mkl/lib/intel64/libmkl_core.a -Wl,--end-group -liomp5 -lpthread -lm -ldl
动态链接：
/opt/intel/compilers_and_libraries_2016/linux/bin/intel64/icpc
-rdynamic CMakeFiles/simplesolver.dir/pardiso_sym_c.cpp.o -o simplesolver
-L/opt/intel/compilers_and_libraries_2016/linux/mkl/lib/intel64 -lmkl_intel_lp64 -lmkl_intel_thread -lmkl_core -liomp5 -lpthread -lm -ldl
这是否存在任何已知问题？还是我们缺少一些用于提高分解性能的编译/链接标志？代码完全相同（MKL发行版中的solverc示例）。我们唯一改变的是如何链接，然后在运行速度上获得了巨大的差异。
我们正在使用Intel Compiler C ++ 2016，并在Linux（Ubuntu 14.04）下使用MKL。我们通过查看PARDISO（msglvl = 1）的输出来测量时间。
只有在有帮助的情况下，这才是代码（我省略了从文件中读取矩阵信息的readData函数）。
#include "mkl_pardiso.h"
#include "mkl_types.h"
#include <cmath>
#include <iomanip>
#include <iostream>
#include <fstream>
#include <string>
MKL_INT main (void)
{
int n; // dimension of matrix
int nnz; // number of non zeroes
int* ia; // coordinates in i of each value in a
int* ja; // coordinates in j of each value in a
double* a; // values of the matrix
double* b; // vector of forces
double* x_expected; // computed solution our software (Ax=rhs)
double* x; // computed solution in pardiso
bool result = false;
std::string fileIn = "problemData.bin";
//METHOD THAT FILLS ALL THE VALUES... NOT RELEVANT.
result = readData(fileIn, n, nnz, &ia, &ja, &a, &b, &x_expected, false);
x = new double[n];
if (!result)
return 1;
MKL_INT mtype = -2; /* Real symmetric matrix */
/* RHS and solution vectors. */
MKL_INT nrhs = 1; /* Number of right hand sides. */
/* Internal solver memory pointer pt, */
/* 32-bit: int pt[64]; 64-bit: long int pt[64] */
/* or void *pt[64] should be OK on both architectures */
void *pt[64];
/* Pardiso control parameters. */
MKL_INT iparm[64];
MKL_INT maxfct, mnum, phase, error, msglvl;
/* Auxiliary variables. */
MKL_INT i;
double ddum; /* Double dummy */
MKL_INT idum; /* Integer dummy. */
/* -------------------------------------------------------------------- */
/* .. Setup Pardiso control parameters. */
/* -------------------------------------------------------------------- */
for ( i = 0; i < 64; i++ )
{
iparm[i] = 0;
}
iparm[0] = 1; /* No solver default */
iparm[1] = 2; /* Fill-in reordering from METIS */
iparm[3] = 0; /* No iterative-direct algorithm */
iparm[4] = 0; /* No user fill-in reducing permutation */
iparm[5] = 0; /* Write solution into x */
iparm[6] = 0; /* Not in use */
iparm[7] = 2; /* Max numbers of iterative refinement steps */
iparm[8] = 0; /* Not in use */
iparm[9] = 13; /* Perturb the pivot elements with 1E-13 */
iparm[10] = 1; /* Use nonsymmetric permutation and scaling MPS */
iparm[11] = 0; /* Not in use */
iparm[12] = 0; /* Maximum weighted matching algorithm is switched-off (default for symmetric). Try iparm[12] = 1 in case of inappropriate accuracy */
iparm[13] = 0; /* Output: Number of perturbed pivots */
iparm[14] = 0; /* Not in use */
iparm[15] = 0; /* Not in use */
iparm[16] = 0; /* Not in use */
iparm[17] = -1; /* Output: Number of nonzeros in the factor LU */
iparm[18] = -1; /* Output: Mflops for LU factorization */
iparm[19] = 0; /* Output: Numbers of CG Iterations */
maxfct = 1; /* Maximum number of numerical factorizations. */
mnum = 1; /* Which factorization to use. */
msglvl = 1; /* Print statistical information in file */
error = 0; /* Initialize error flag */
/* -------------------------------------------------------------------- */
/* .. Initialize the internal solver memory pointer. This is only */
/* necessary for the FIRST call of the PARDISO solver. */
/* -------------------------------------------------------------------- */
for ( i = 0; i < 64; i++ )
{
pt[i] = 0;
}
/* -------------------------------------------------------------------- */
/* .. Reordering and Symbolic Factorization. This step also allocates */
/* all memory that is necessary for the factorization. */
/* -------------------------------------------------------------------- */
phase = 11;
PARDISO (pt, &maxfct, &mnum, &mtype, &phase,
&n, a, ia, ja, &idum, &nrhs, iparm, &msglvl, &ddum, &ddum, &error);
if ( error != 0 )
{
printf ("\nERROR during symbolic factorization: %d", error);
return -1;
}
printf ("\nReordering completed ... ");
printf ("\nNumber of nonzeros in factors = %d", iparm[17]);
printf ("\nNumber of factorization MFLOPS = %d", iparm[18]);
/* -------------------------------------------------------------------- */
/* .. Numerical factorization. */
/* -------------------------------------------------------------------- */
phase = 22;
PARDISO (pt, &maxfct, &mnum, &mtype, &phase,
&n, a, ia, ja, &idum, &nrhs, iparm, &msglvl, &ddum, &ddum, &error);
if ( error != 0 )
{
printf ("\nERROR during numerical factorization: %d", error);
return -2;
}
printf ("\nFactorization completed ... ");
/* -------------------------------------------------------------------- */
/* .. Back substitution and iterative refinement. */
/* -------------------------------------------------------------------- */
phase = 33;
iparm[7] = 2; /* Max numbers of iterative refinement steps. */
PARDISO (pt, &maxfct, &mnum, &mtype, &phase,
&n, a, ia, ja, &idum, &nrhs, iparm, &msglvl, b, x, &error);
if ( error != 0 )
{
printf ("\nERROR during solution: %d", error);
return -3;
}
printf ("\nSolve completed ... ");
/* -------------------------------------------------------------------- */
/* .. Termination and release of memory. */
/* -------------------------------------------------------------------- */
phase = -1; /* Release internal memory. */
PARDISO (pt, &maxfct, &mnum, &mtype, &phase,
&n, &ddum, ia, ja, &idum, &nrhs,
iparm, &msglvl, &ddum, &ddum, &error);
delete [] ia;
delete [] ja;
delete [] a;
delete [] b;
delete [] x;
delete [] x_expected;
return 0;
}
答案 0 :(得分：0)
您已启用0个优化。然后，很多因素将导致与MKL /动态链接与静态链接等都不相关的运行时行为。当您使用-O2 -g -march=native，-O3 -march=native编译上述代码时，会发生什么情况？差异应完全消除。