cholesky decomposition ScaLapack error(Cholesky 分解 ScaLapack 错误)
问题描述
我收到以下错误，我不知道为什么.
I'm getting the following error and i'm not sure why.
{ 1, 1}: On entry to PDPOTRF parameter number 2 had an illegal value
{ 1, 0}: On entry to PDPOTRF parameter number 2 had an illegal value
{ 0, 1}: On entry to PDPOTRF parameter number 2 had an illegal value
{ 0, 0}: On entry to PDPOTRF parameter number 2 had an illegal value
info < 0: If the i-th argument is an array and the j-entry had an illegal value, then INFO = -(i*100+j), if the i-th argument is a scalar and had an illegal value, then INFO = -i.
我知道错误消息的含义，但我尽可能遵循网络上可用的过时文档，并尝试从网络上的工作示例代码中拼凑出并行的 Cholesky 分解.我不确定我哪里出错了.
I Know what the error messages means but I followed the dated documentation available on the web as best as possible and tried to piece together a parallel cholesky factorization from working example codes on the web. I'm not sure where I went wrong.
有人能解释一下我在下面的代码中哪里出错了吗?这是代码功能的概述，我正在使用 4 个处理器进行测试，并将 8x8 矩阵划分为 2 x 2 处理器块网格从文件中加载一个矩阵，这里有一个 8 x 8 matrixfile 的例子，
Could some one explain where I went wrong in the code below? Here's an overview of what the code does, I'm testing with 4 processors and divide the 8x8 matrix into 2 x 2 processor block grid loads a matrix from file, heres an example 8 x 8 matrixfile ,
182 147 140 125 132 76 126 157
147 213 185 150 209 114 166 188
140 185 232 129 194 142 199 205
125 150 129 143 148 81 104 150
132 209 194 148 214 122 172 189
76 114 142 81 122 102 129 117
126 166 199 104 172 129 187 181
157 188 205 150 189 117 181 259
我按照示例将矩阵分配到 4 个单独的 4x4 本地阵列，每个阵列分别位于 4 个节点上.然后我运行 descinit_ 并调用产生上述错误的相关 pdpotrf_ 例程.我不知道我哪里出错了，并尽可能地遵循文档.Fortran 中并行 Cholesky 分解的工作示例也将有很大帮助
I followed examples to distribute the Matrix to 4 separate 4x4 local arrays one on each of the 4 nodes. I then run descinit_ and call the associated pdpotrf_ routine which yields the above error. I have no idea where i went wrong and tried to follow documentation as best as I could. A working example of a parallel cholesky decomposition in fortran would also greatly help
函数调用参考
pdpotrf_
descinit_
运行参数
code name - Meaning = Value
N - Global Rows = 8
M - Global Cols = 8
Nb - Local Block Rows = 2
Mb - Local Block Cols = 2
nrows - Local Rows = 4
ncols Local Cols= 4
lda - Leading dimension of local array = 4 (i've tried 2,4,8)
ord - Order of Matrix = 4 (i've also tried many different things here as well)
我在每个节点上都打印了上面的参数，它们都是一样的
I Printed the above parameters on every node and they are the same
#include <mpi.h>
#include <iostream>
#include <iomanip>
#include <string>
#include <fstream>
#include <iostream>
#include <stdlib.h>
#include <sstream>
using namespace std;
/*
To compile:
mpic++ test.cpp -o test -L/home/admin/libs -lscalapack -lrefblas -ltmg -lreflapack -lgfortran -Wall -O2
To run:
mpirun -np 4 ./test matrixfile 8 8 2 2
*/
extern "C" {
/* Cblacs declarations */
void Cblacs_pinfo(int*, int*);
void Cblacs_get(int, int, int*);
void Cblacs_gridinit(int*, const char*, int, int);
void Cblacs_gridinfo(int, int*, int*, int*,int*);
void Cblacs_pcoord(int, int, int*, int*);
void Cblacs_gridexit(int);
void Cblacs_barrier(int, const char*);
void Cdgerv2d(int, int, int, double*, int, int, int);
void Cdgesd2d(int, int, int, double*, int, int, int);
int numroc_(int*, int*, int*, int*, int*);
void pdpotrf_(char*, int*, double*,
int*, int*, int*, int*);
void descinit_( int *, int *, int *, int *, int *, int *, int *,
int *, int *, int *);
}
int main(int argc, char **argv){
/* MPI */
int mpirank,nprocs;
MPI_Init(&argc, &argv);
MPI_Comm_rank(MPI_COMM_WORLD, &mpirank);
MPI_Comm_size(MPI_COMM_WORLD, &nprocs);
double MPIelapsed;
double MPIt2;
double MPIt1;
/* Helping vars */
int iZERO = 0;
int verbose = 1;
bool mpiroot = (mpirank == 0);
if (argc < 6) {
if (mpiroot)
cerr << "Usage: matrixTest matrixfile N M Nb Mb"
<< endl
<< " N = Rows , M = Cols , Nb = Row Blocks , Mb = Col Blocks "
<< endl;
MPI_Finalize();
return 1;
}
/* Scalapack / Blacs Vars */
int N, M, Nb, Mb;
int descA[9];
int info = 0;
// int mla = 4;
int ord = 8;
double *A_glob = NULL, *A_glob2 = NULL, *A_loc = NULL;
/* Parse command line arguments */
if (mpiroot) {
/* Read command line arguments */
stringstream stream;
stream << argv[2] << " " << argv[3] << " " << argv[4] << " " << argv[5];
stream >> N >> M >> Nb >> Mb;
/* Reserve space and read matrix (with transposition!) */
A_glob = new double[N*M];
A_glob2 = new double[N*M];
string fname(argv[1]);
ifstream file(fname.c_str());
for (int r = 0; r < N; ++r) {
for (int c = 0; c < M; ++c) {
file >> *(A_glob + N*c + r);
}
}
/* Print matrix */
if(verbose == 1) {
cout << "Matrix A:
";
for (int r = 0; r < N; ++r) {
for (int c = 0; c < M; ++c) {
cout << setw(3) << *(A_glob + N*c + r) << " ";
}
cout << "
";
}
cout << endl;
}
}
/* Begin Cblas context */
int ctxt, myid, myrow, mycol, numproc;
//<TODO> make dynamic
int procrows = 2, proccols = 2;
Cblacs_pinfo(&myid, &numproc);
Cblacs_get(0, 0, &ctxt);
Cblacs_gridinit(&ctxt, "Row-major", procrows, proccols);
Cblacs_gridinfo( ctxt, &procrows, &proccols, &myrow, &mycol );
/* process coordinates for the process grid */
// Cblacs_pcoord(ctxt, myid, &myrow, &mycol);
/* Broadcast of the matrix dimensions */
int dimensions[4];
if (mpiroot) {
dimensions[0] = N;//Global Rows
dimensions[1] = M;//Global Cols
dimensions[2] = Nb;//Local Rows
dimensions[3] = Mb;//Local Cols
}
MPI_Bcast(dimensions, 4, MPI_INT, 0, MPI_COMM_WORLD);
MPI_Bcast(&ord, 1, MPI_INT, 0, MPI_COMM_WORLD);
N = dimensions[0];
M = dimensions[1];
Nb = dimensions[2];
Mb = dimensions[3];
int nrows = numroc_(&N, &Nb, &myrow, &iZERO, &procrows);
int ncols = numroc_(&M, &Mb, &mycol, &iZERO, &proccols);
int lda = max(1,nrows);
MPI_Bcast(&lda, 1, MPI_INT, 0, MPI_COMM_WORLD);
/* Print grid pattern */
if (myid == 0)
cout << "Processes grid pattern:" << endl;
for (int r = 0; r < procrows; ++r) {
for (int c = 0; c < proccols; ++c) {
Cblacs_barrier(ctxt, "All");
if (myrow == r && mycol == c) {
cout << myid << " " << flush;
}
}
Cblacs_barrier(ctxt, "All");
if (myid == 0)
cout << endl;
}
if(myid == 0){
cout <<"Run Parameters"<<endl;
cout <<"Global Rows = " << M <<endl;
cout <<"Global Cols = " << N <<endl;
cout <<"Local Block Rows = " << Mb <<endl;
cout <<"Local Block Cols = " << Nb <<endl;
cout << "nrows = "<<nrows<<endl;
cout << "ncols = "<<ncols<<endl;
cout << "lda = "<<lda<<endl;
cout <<"Order = "<<ord<<endl;
}
for (int id = 0; id < numproc; ++id) {
Cblacs_barrier(ctxt, "All");
}
A_loc = new double[nrows*ncols];
for (int i = 0; i < nrows*ncols; ++i) *(A_loc+i)=0.;
/* Scatter matrix */
int sendr = 0, sendc = 0, recvr = 0, recvc = 0;
for (int r = 0; r < N; r += Nb, sendr=(sendr+1)%procrows) {
sendc = 0;
int nr = Nb;
if (N-r < Nb)
nr = N-r;
for (int c = 0; c < M; c += Mb, sendc=(sendc+1)%proccols) {
int nc = Mb;
if (M-c < Mb)
nc = M-c;
if (mpiroot) {
Cdgesd2d(ctxt, nr, nc, A_glob+N*c+r, N, sendr, sendc);
}
if (myrow == sendr && mycol == sendc) {
Cdgerv2d(ctxt, nr, nc, A_loc+nrows*recvc+recvr, nrows, 0, 0);
recvc = (recvc+nc)%ncols;
}
}
if (myrow == sendr)
recvr = (recvr+nr)%nrows;
}
/* Print local matrices */
if(verbose == 1) {
for (int id = 0; id < numproc; ++id) {
if (id == myid) {
cout << "A_loc on node " << myid << endl;
for (int r = 0; r < nrows; ++r) {
for (int c = 0; c < ncols; ++c)
cout << setw(3) << *(A_loc+nrows*c+r) << " ";
cout << endl;
}
cout << endl;
}
Cblacs_barrier(ctxt, "All");
}
}
for (int id = 0; id < numproc; ++id) {
Cblacs_barrier(ctxt, "All");
}
/* DescInit */
info=0;
descinit_(descA, &N, &M, &Nb, &Mb,&iZERO,&iZERO,&ctxt, &lda, &info);
if(mpiroot){
if(verbose == 1){
if (info == 0){
cout<<"Description init sucesss!"<<endl;
}
if(info < 0){
cout <<"Error Info < 0: if INFO = -i, the i-th argument had an illegal value"<< endl
<<"Info = " << info<<endl;
}
}
// Cblacs_barrier(ctxt, "All");
}
//psgesv_(n, 1, al, 1,1,idescal, ipiv, b, 1,1,idescb, info) */
// psgesv_(&n, &one, al, &one,&one,idescal, ipiv, b, &one,&one,idescb, &info);
//pXelset http://www.netlib.org/scalapack/tools/pdelset.f
/* CHOLESKY HERE */
info = 0;
MPIt1=MPI_Wtime();
pdpotrf_("L",&ord,A_loc,&Nb,&Mb,descA,&info);
for (int id = 0; id < numproc; ++id) {
Cblacs_barrier(ctxt, "All");
}
MPIt2 = MPI_Wtime();
MPIelapsed=MPIt2-MPIt1;
if(mpiroot){
std::cout<<"Cholesky MPI Run Time" << MPIelapsed<<std::endl;
if(info == 0){
std::cout<<"SUCCESS"<<std::endl;
}
if(info < 0){
cout << "info < 0: If the i-th argument is an array and the j-entry had an illegal value, then INFO = -(i*100+j), if the i-th argument is a scalar and had an illegal value, then INFO = -i. " << endl;
cout<<"info = " << info << endl;
}
if(info > 0){
std::cout<<"matrix is not positve definte"<<std::endl;
}
}
//sanity check set global matrix to zero before it's recieved by nodes
if(mpiroot){
for (int r = 0; r < N; ++r) {
for (int c = 0; c < M; ++c) {
A_glob2[c *N + r] = 0;
}
}
}
/* Gather matrix */
sendr = 0;
for (int r = 0; r < N; r += Nb, sendr=(sendr+1)%procrows) {
sendc = 0;
// Number of rows to be sent
// Is this the last row block?
int nr = Nb;
if (N-r < Nb)
nr = N-r;
for (int c = 0; c < M; c += Mb, sendc=(sendc+1)%proccols) {
// Number of cols to be sent
// Is this the last col block?
int nc = Mb;
if (M-c < Mb)
nc = M-c;
if (myrow == sendr && mycol == sendc) {
// Send a nr-by-nc submatrix to process (sendr, sendc)
Cdgesd2d(ctxt, nr, nc, A_loc+nrows*recvc+recvr, nrows, 0, 0);
recvc = (recvc+nc)%ncols;
}
if (mpiroot) {
// Receive the same data
// The leading dimension of the local matrix is nrows!
Cdgerv2d(ctxt, nr, nc, A_glob2+N*c+r, N, sendr, sendc);
}
}
if (myrow == sendr)
recvr = (recvr+nr)%nrows;
}
/* Print test matrix */
if (mpiroot) {
if(verbose == 1){
cout << "Matrix A test:
";
for (int r = 0; r < N; ++r) {
for (int c = 0; c < M; ++c) {
cout << setw(3) << *(A_glob2+N*c+r) << " ";
}
cout << endl;
}
}
}
/* Release resources */
delete[] A_glob;
delete[] A_glob2;
delete[] A_loc;
Cblacs_gridexit(ctxt);
MPI_Finalize();
}
推荐答案
好吧 - 我解决了这个问题.这是你必须做的(我检查了修改后的 MPI 程序的结果与 Octave 中矩阵的 Cholesky 解压缩 - 它有效.).
Right - I solved this. Here's what you have to do (I checked the result of the modified MPI program against a Cholesky decomp of your matrix in Octave -- it works.).
我发现 IBM 提供的以下 LAPACK 参考资料比您链接中的参考资料更有帮助:http://publib.boulder.ibm.com/infocenter/clresctr/vxrx/index.jsp?topic=%2Fcom.ibm.cluster.pessl.v4r2.pssl100.doc%2Fam6gr_lpotrf.htm
I found the following LAPACK reference by IBM to be more helpful than the one in your link: http://publib.boulder.ibm.com/infocenter/clresctr/vxrx/index.jsp?topic=%2Fcom.ibm.cluster.pessl.v4r2.pssl100.doc%2Fam6gr_lpotrf.htm
PDPOTRF(UPLO, N, A, IA, JA, DESCA, INFO)
您将 Mb 和 Nb 作为 IA 和 JA 传递.但是，这些参数旨在在更大的矩阵中提供全局矩阵的起始行和列.仅当您有一个大矩阵并且只想要子矩阵的 Cholesky 分解时，它们才相关.在您的情况下， IA 和 JA 都必须是 1!
You are passing Mb and Nb as IA and JA. However, those parameters are meant to provide the starting row and column of your global matrix inside a larger matrix. They are only relevant if you have a big matrix and only want the Cholesky decomp of a submatrix. In your case, IA and JA both have to be 1!
所以你需要做的就是:
int IA = 1;
int JA = 1;
pdpotrf_("L",&ord,A_loc,&IA,&JA,descA,&info);
您可能还想更改硬编码的 int ord = 8; 使其取决于从命令行读取的值，否则您以后会遇到问题.
You may also want to change your hardcoded int ord = 8; so that it depends on the value read from the command line, otherwise you'll run into problems later.
如上所述修改程序的输出:
Output of your program modified as described above:
Cholesky MPI Run Time0.000659943
SUCCESS
Matrix A test:
13.4907 147 140 125 132 76 126 157
10.8964 9.70923 185 150 209 114 166 188
10.3775 7.4077 8.33269 129 194 142 199 205
9.26562 5.0507 -0.548194 5.59806 148 81 104 150
9.78449 10.5451 1.72175 0.897537 1.81524 122 172 189
5.63349 5.41911 5.20784 0.765767 0.0442447 3.63139 129 117
9.33974 6.61543 6.36911 -2.22569 1.03941 2.48498 1.79738 181
11.6376 6.30249 4.50561 2.28799 -0.627688 -2.17633 7.27182 0.547228
用于比较的八度输出:
octave:1> A=dlmread("matrixfile4")
A =
182 147 140 125 132 76 126 157
147 213 185 150 209 114 166 188
140 185 232 129 194 142 199 205
125 150 129 143 148 81 104 150
132 209 194 148 214 122 172 189
76 114 142 81 122 102 129 117
126 166 199 104 172 129 187 181
157 188 205 150 189 117 181 259
octave:2> C=chol(A)
C =
13.49074 10.89636 10.37749 9.26562 9.78449 5.63349 9.33974 11.63761
0.00000 9.70923 7.40770 5.05070 10.54508 5.41911 6.61543 6.30249
0.00000 0.00000 8.33269 -0.54819 1.72175 5.20784 6.36911 4.50561
0.00000 0.00000 0.00000 5.59806 0.89754 0.76577 -2.22569 2.28799
0.00000 0.00000 0.00000 0.00000 1.81524 0.04424 1.03941 -0.62769
0.00000 0.00000 0.00000 0.00000 0.00000 3.63139 2.48498 -2.17633
0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 1.79738 7.27182
0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.54723
(我之前关于矩阵被错误复制到节点的评论 - 现在已删除 - 不适用，你的程序的其余部分对我来说似乎很好.)
(My earlier comment -now deleted- about matrices being wrongly copied to the nodes does not apply, the rest of your program seems fine to me.)
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本文标题为：Cholesky 分解 ScaLapack 错误
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